Stigmergy Facilitates Emergent Patterns in Academic Communication

Stigmergy Facilitates Emergent Patterns in Academic Communication | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Stigmergy Facilitates Emergent Patterns in Academic Communication Marvin Starominski-Uehara This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7153879/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study applies stigmergic principles to examine human stigmergy research itself, treating academic papers as environmental traces. Through systematic analysis, this investigation reveals how scholars function as autonomous agents depositing intellectual ‘pheromones’ through publications, creating pathways that guide collective knowledge advancement. Using three progressive ranking methodologies, the study demonstrates that foundational theoretical papers create stronger, more persistent pathways than applied studies. The analysis validates that researchers strategically engaging with established theoretical pathways achieve higher scholarly fitness, offering insights for organizing collaborative intelligence systems. Biological sciences/Psychology Social science/Psychology Social science/Science technology and society stigmergy collective intelligence indirect coordination academic knowledge networks self-organization Figures Figure 1 Highlights Theoretical papers create stronger, more persistent citation pathways than applied studies Citing influential theoretical works enhances researchers' scholarly impact and fitness Decentralized citation behaviors drive coherent research directions through invisible synchrony Introduction Just as termites construct complex mounds through individual actions that modify their environment (Grassé 1959), academic researchers function as autonomous agents leaving intellectual 'pheromones' in digital scholarly environments through their publications. The originality of this approach lies in recognizing that academic papers themselves serve as stigmergic traces -- environmental modifications that facilitate trace-based communication across temporal and spatial boundaries. When Pierre-Paul Grassé published the theory of stigmergy in 1959, he was not merely documenting a biological phenomenon; the French zoologist was sharing a cue in the academic environment that would guide himself and subsequent researchers toward productive research territories. Grassé’s (1959) foundational paper, with 1907 citations, is evidence of its stigmergic potency and path formation influence. In the framework of this study, citing researchers function as foraging agents within collaborative networks, actively seeking information traces to meet their immediate scholarly goals. These agents encounter existing papers -- the pheromone trails left by themselves or previous researchers -- and make autonomous decisions about whether to follow, reinforce, or ignore these traces based on their relevance to current objectives. The act of citation represents social signaling and pheromone reinforcement, strengthening certain pathways in the knowledge landscape while allowing others to decay through neglect. This process exhibits stigmergic characteristics of self-organization: individual researchers operate autonomously without direct coordination, yet their collective citing behaviors create emergent patterns that guide the field's development. Papers like 'A Brief History of Stigmergy' (1999, 876 citations) by Guy Theraulaz and Eric Bonabeau, H. Van Dyke Parunak's 'Survey of Environments and Mechanisms for Human-Human Stigmergy' (2005, 225 citations) and ‘Stigmergy as a Universal Coordination Mechanism: Components, Varieties and Applications’ by Francis Heylighen (2015, 76 citations) function as major thoroughfares in this intellectual landscape, demonstrating how decentralization in scholarly activity produces coherent directional flows. This investigation addresses two interconnected research questions: (i) Which academic traces (papers) have created the most influential pheromone pathways in human stigmergy research, as evidenced by sustained citation reinforcement and path formation? (ii) How does strategic pheromone-following behavior (citing influential foundational works) enhance the environmental impact and scholarly fitness of citing agents through indirect coordination mechanisms? These questions recognize that not all academic traces possess equal stigmergic potential. Some papers, particularly foundational theoretical works, create persistent, high-concentration pheromone trails that continue attracting researchers across multiple generations through sustained trace-based communication, while others represent weak or ephemeral cues that fail to coordinate significant collective behavior. As for hypotheses, they reflect stigmergic principles governing trace persistence and agent coordination: (i) Foundational theoretical papers create stronger, more persistent pheromone trails than applied studies, evidenced by sustained citation reinforcement over time, as these works address fundamental coordination mechanisms rather than specific applications; (ii) Researchers who strategically follow established pheromone trails (cite foundational works) produce more impactful environmental modifications (higher-quality, more-cited papers), as they build upon proven collaborative networks rather than creating isolated traces. This stigmergic analysis of human stigmergy research also represents a methodological innovation that transcends traditional bibliometric approaches. By examining a dataset of 93 papers, it demonstrates how autonomous scholarly agents have collectively constructed a knowledge 'nest' spanning collective intelligence, computer science, urban planning, and digital humanities through self-organization and emergence. This investigation yields conceptual lessons demonstrating that invisible synchrony governs scholarly knowledge construction, where individual researcher decisions aggregate into coherent disciplinary directions through trace-based communication. For the scientific community, this reveals how decentralization can enhance knowledge advancement, suggesting and strengthening models for research coordination that leverage cues and social signaling. Methods A systematic literature search was conducted using Google Scholar i with the exact term ‘human stigmergy’ to maintain specificity and avoid diluting results with tangentially related research. The search was performed in May 2025 to capture the most recent publications. To ensure comprehensive coverage, the search was extended to eight additional languages: Portuguese, French, Spanish, Italian, Japanese, Chinese, Swedish, and German, yielding a total of 1,289 initial entries across all languages ii . Papers were included if they: (i) explicitly addressed ‘stigmergy’ in the title, abstract, or keywords; (ii) were published in peer-reviewed journals, conference proceedings, or reputable grey literature; (iii) had at least one citation to ensure minimum academic engagement; and (iv) were available in full text. Papers were excluded if they: (i) lacked clear focus on human stigmergy; (ii) were from non-academic sources; (iii) had zero citations indicating absence of social signaling; or (iv) were inaccessible in full text. Following PRISMA guidelines (see Image 1), the initial pool of 1,289 entries was systematically screened, resulting in 93 papers meeting the inclusion criteria. Six papers were deemed ‘partially related’ to human stigmergy but included due to their foundational importance, such as Theraulaz and Bonabeau's ‘A Brief History of Stigmergy’ (1999). Each paper was systematically analyzed to extract: (i) publication metadata (author, year, language, publisher); (ii) citation patterns within the corpus; (iii) theoretical versus applied focus; and (iv) disciplinary categorization (See Graph 2). Papers were classified as either theoretical (establishing frameworks, principles, or taxonomies) or applied (implementing stigmergic concepts in specific domains or technologies). This study introduces a three-tier ranking methodology (see 'Results') to systematically evaluate pheromone pathway formation and scholarly fitness enhancement, progressively refining the analysis from broad citation patterns to specialized field-specific coordination behaviors. The analysis incorporated the following validation measures to ensure methodological rigor: (i) quality assessment was performed using a customized tool adapted from the Critical Appraisal Skills Program (CASP) (See Graph 3); (ii) the composite scoring methodology balanced recent contributions against established works to mitigate temporal bias; (iii) the 93 papers represented multiple languages, indicating reasonable geographic and linguistic diversity; and (iv) the corpus included both foundational theoretical works and practical applications, enabling comparative analysis of pathway formation patterns across different research approaches. Results First Ranking: Identifying the Strongest Pheromone Pathways To objectively address the first research question regarding which academic traces have created the most influential pheromone pathways, this study rephrased the inquiry as: 'Which papers function as the strongest pheromone trails through sustained cross-citation reinforcement within human stigmergy research via trace-based communication?' This reformulation allowed assessment of which selected academic traces contributed most significantly to distributed knowledge construction. All citations from the final 93 selected papers were collected and tabulated as evidence of pheromone-following behavior. After checking for cross-referencing patterns, this total was reduced to 17 papers representing the most concentrated ‘pheromone’ trails. Table 1: Ranking of Cross-Cited Human Stigmergy Papers Rank Paper Title Year Citation Count Older More Conceptual 1 A Brief History of Stigmergy 1999 876 Yes Yes 2 A Survey of Environments and Mechanisms for Human-Human Stigmergy 2005 225 Yes Yes 3 Stigmergy as a Universal Coordination Mechanism: components, varieties and applications 2015 76 No Yes 4 Sleep behavior assessment via smartwatch and stigmergic receptive fields 2017 66 No No 5 Self-Organized Trail Systems in Groups of Humans 2006 59 Yes Yes 6 Group Path Formation 2006 58 Yes Yes 7 Silent Agents: From Observation to Tacit Communication 2006 44 Yes Yes 8 MARS, a Multi-Agent System for Assessing Rowers' Coordination: Coordination via Motion-Based Stigmergy 2013 38 No Yes 9 General Theory of Stigmergy: Modelling Stigma Semantics 2014 38 No Yes 10 Bacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria 2015 35 No Yes 11 Cultural-Historical Perspectives on Collective Intelligence 2021 33 No Yes 12 Improving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution 2015 30 No No 13 Multi-Agent Cooperation Using the Ant Algorithm with Variable Pheromone Placement 2005 19 Yes No 14 Engineering Human Stigmergy 2015 18 No No 15 Phenotropic and stigmergic webs: the new reach of networks 2011 17 No Yes 16 Cognitive Maps for Indirect Coordination of Intelligent Agents 2015 9 No Yes 17 Online Activity Recognition Combining Dynamic Segmentation and Emergent Modeling 2022 8 No No The analysis revealed that foundational theoretical papers create stronger, more persistent pheromone trails than applied studies, as evidenced by sustained citation reinforcement over time through trace-based communication. The most influential pheromone pathway was created by 'A Brief History of Stigmergy' (Theraulaz & Bonabeau 1999, 876 citations), which helped establish stigmergy's fundamental theoretical framework by explaining indirect coordination mechanisms in social insects through environmental traces such as pheromones and nest structures, while suggesting broader applications to human systems including trail formation and collaborative construction through self-organization. This academic trace functions as a major ‘trace’ in the intellectual landscape, continuously attracting foraging researchers through its high-concentration digital cues. The second-strongest pathway, 'A Survey of Environments and Mechanisms for Human-Human Stigmergy' (Van Dyke Parunak 2005:3, 225 citations), reinforces the pattern by providing a taxonomy of stigmergic interactions specifically within human contexts, systematically distinguishing between marker-based: ‘special markers that agents deposit in the environment’ versus sematectonic iii stigmergy: ‘whether agents base their actions on the current state of the solution’ and quantitative iv (‘whether the signals are a single scalar analogous to a potential field’) versus qualitative v variations (‘whether they form a set of discrete options’) via trace-based communication. These interactions demonstrate how specialized theoretical contributions can create persistent pathways through trace-based communication in specific research territories using digital cues. The third-ranked paper, 'Stigmergy as a Universal Coordination Mechanism' (2015, 76 citations), further validates the pathway-forming capacity of theoretical contributions by offering a framework that positions stigmergy as a coordination mechanism enabling complex organization across human and non-human domains. This work specifically addresses human cognition through external memory systems and collaborative platforms like Wikipedia, showing how stigmergic principles scale to digital environments. Examining the complete ranking revealed that five of the top seven papers are both older (published before 2010) and conceptual in nature, collectively accounting for 1,262 citations out of the total 1,649 citations across all ranked papers -- representing 77% of the total pheromone concentration through emergence patterns. In contrast, newer applied studies, such as smartwatch-based sleep behavior assessment (rank 4) and computational approaches to activity recognition (rank 17), while technically innovative, have achieved relatively modest citation counts despite their practical applications, indicating weaker path formation capabilities. This pheromone distribution pattern confirms that theoretical contributions establishing core principles, frameworks, and taxonomies of human stigmergy create substantial and persistent pathways through environmental trace deposition via cues, with foundational works continuing to attract foraging researchers and influence contemporary research directions. Second Ranking: Normalizing Pathway Strength by Field-Specific Reinforcement The second ranking refined pathway analysis by examining how frequently each of the 93 selected papers engaged in cross-citation behavior -- self-citation vi was only marginally observed in this dataset -- as evidence of pheromone-following within the specific research environment. This frequency ('Appearances') was normalized with total citation counts to re-rank the remaining 17 papers, revealing the distinction between broad academic impact and concentrated path formation within the human stigmergy research ecosystem through self-organization. Table 2: Ranking of Cross-Cited Human Stigmergy Papers Normalized by Frequency Rank Paper Title Appearances Norm. Citation Norm. Appearances Combined Score 1 A Brief History of Stigmergy 13 1 1 1 2 A Survey of Environments and Mechanisms for Human-Human Stigmergy 10 0.2517 0.75 0.5009 3 Stigmergy as a Universal Coordination Mechanism: components, varieties and applications 3 0.0787 0.1667 0.1227 4 MARS, a Multi-Agent System for Assessing Rowers' Coordination: Coordination via Motion-Based Stigmergy 3 0.0347 0.1667 0.1007 5 Group Path Formation 2 0.0578 0.0833 0.0706 6 General Theory of Stigmergy: Modelling Stigma Semantics 2 0.0347 0.0833 0.059 7 Cultural-Historical Perspectives on Collective Intelligence 2 0.0289 0.0833 0.0561 8 Improving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution 2 0.0254 0.0833 0.0544 9 Engineering Human Stigmergy 2 vii 0.0116 0.0833 0.0474 10 Cognitive Maps for Indirect Coordination of Intelligent Agents 2 viii 0.0012 0.0833 0.0422 11 Sleep behavior assessment via smartwatch and stigmergic receptive fields 1 ix 0.0671 0 0.0335 12 Self-organized Trail Systems in Groups of Humans 1 0.0589 0 0.0295 13 Silent Agents: From Observation to Tacit Communication 1 0.0416 0 0.0208 14 Bacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria 1 0.0312 0 0.0156 15 Multi-Agent Cooperation Using the Ant Algorithm with Variable Pheromone Placement 1 0.0127 0 0.0064 16 Phenotropic and stigmergic webs: the new reach of networks 1 0.0104 0 0.0052 17 Online Activity Recognition Combining Dynamic Segmentation and Emergent Modeling 1 0 0 0 The normalized frequency analysis exposed shifts that provide nuanced insights into pheromone pathway formation. While foundational theoretical traces maintained dominance, the analysis revealed distinctions between broader academic visibility and concentrated pathway reinforcement within the human stigmergy research community. 'A Brief History of Stigmergy' (Theraulaz & Bonabeau 1999) maintained its position through both pheromone concentration (876 citations) and frequent reinforcement by foraging agents (13 appearances) via social signaling. This trace's sustained influence demonstrates how foundational environmental modifications continue to coordinate research behavior across multiple scholar generations through persistent high-concentration pathways and emergence patterns. 'A Survey of Environments and Mechanisms for Human-Human Stigmergy' (Van Dyke Parunak 2005) strengthened its position with a combined score of 0.5009, appearing as a reference point for 10 out of 93 papers through collaborative networks. This enhanced ranking reflected the work's critical role as a coordination mechanism, bridging biological stigmergy concepts to human contexts through systematic taxonomies that enable indirect coordination among researchers via digital cues. The normalized analysis, however, revealed distinct patterns in how theoretical versus applied traces function within the stigmergic research environment. Applied studies such as 'Sleep Behavior Assessment Via Smartwatch and Stigmergic Receptive Fields' (Alfeo et al. 2018) (dropped from 4th to 11th) and 'Self-Organized Trail Systems in Groups of Humans' (Goldstone & Roberts 2006) (dropped from 5th to 12th) suggesting that substantial pheromone concentrations do not necessarily translate into sustained pathway reinforcement within the specialized field through trace-based communication. Conversely, newer theoretical traces like 'MARS, a Multi-Agent System for Assessing Rowers' Coordination' (Avvenuti et al. 2013) rose from 8th to 4th position, suggesting that theoretical contributions x with direct human stigmergy applications maintain stronger coordination functions as demonstrated by the MARS system, which uses motion-based stigmergy to assess rowing asynchrony in a shared sensing space. The most significant insight concerns highly cited but less field-relevant studies. Papers focusing on computational applications of stigmergic principles to human behavioral data, while achieving substantial citation counts, experienced dramatic ranking drops when field-specific cross-referencing was considered. This pattern indicated that technical implementations, though academically successful, may not directly advance theoretical understanding of interdisciplinary human stigmergy mechanisms. The refined ranking provided stronger empirical support for the principle that theoretical traces create more persistent and concentrated pheromone pathways in human stigmergy research. Top-ranking environmental modifications consistently focus on foundational frameworks -- from Theraulaz and Bonabeau's (1999) biological principles to Van Dyke Parunak's (2005) human-specific taxonomies and Heylighen's (2015) universal coordination mechanisms -- rather than specific technical applications. This demonstrated that conceptual contributions maintain their coordination capacity within the specialized research community, serving as essential navigation points that shape ongoing theoretical development and empirical investigation. Third Ranking: Analyzing Strategic Pheromone-Following Behavior and Scholarly Fitness The third ranking addressed the second research question regarding how strategic pheromone-following behavior enhances the environmental impact and scholarly fitness of citing agents through indirect coordination mechanisms. This analysis examined how researchers functioning as foraging agents can improve their own environmental modifications (paper quality and citation impact) by strategically following established pheromone trails (citing influential foundational works). The 32 papers selected for this assessment represent citing agents that engaged in cross-referencing (including self-citation) behavior at least once among the 93 selected papers, demonstrating active pheromone-following within the research environment through trace-based communication. A composite scoring method, designed to objectively assess fitness enhancement via strategic coordination, was developed by incorporating four equally weighted components: Year Published, Total Number of Citations, Number of Citations by Human Stigmergy Articles, and the Sum of Citations of Cited Human Stigmergy Articles. Table 3: Ranking of Citing Papers Normalized by Year Published, Total Citations, Human Stigmergy Citations, and Sum of Citing Articles’ Citations Rank Paper Title Year Published Total Citations Human Stigmergy Citations Sum of Citing Articles' Citations Score 1 A Stigmergy-Based Analysis of City Hotspots to Discover Trends and Anomalies in Urban Transportation Usage 2018 37 3 972 0.6097 2 Bacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria 2015 35 3 1160 0.5942 3 General Theory of Stigmergy: Modelling Stigma Semantics 2014 38 3 1120 0.5847 4 Cultural-Historical Perspectives on Collective Intelligence 2021 33 2 952 0.5574 5 Cooperation and deception through stigmergic interactions in human groups 2023 4 3 944 0.5408 6 Sleep behavior assessment via smartwatch and stigmergic receptive fields 2018 66 2 68 0.5239 7 Stigmergy as a Universal Coordination Mechanism: components, varieties and applications 2015 76 1 38 0.5236 8 Ant Colonies: Building Complex Organizations with Minuscule Brains and No Leaders 2021 29 1 876 0.5151 9 Pervasive Pheromone-Based Interaction with RFID Tags 2007 93 1 225 0.4969 10 The inheritance of alternative nest architectural traditions in stingless bees 2024 7 1 876 0.4817 11 Joint action in an elite rowing pair crew after intensive team training 2018 22 2 76 0.466 12 Can we identify general architectural principles that impact the collective behaviour of both human and animal systems? 2018 15 1 876 0.4645 13 Micro-Patterned Surfaces That Exploit Stigmergy to Inhibit Biofilm Expansion 2017 15 1 876 0.4456 14 Improving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution 2015 30 2 263 0.4349 15 MARS, a Multi-Agent System for Assessing Rowers' Coordination: Coordination via Motion-Based Stigmergy 2013 38 1 263 0.432 16 Self-Organization Leads to Supraoptimal Performance in Public Transportation Systems 2011 39 1 876 0.4263 17 Education for Collective Intelligence 2025 11 1 33 0.37 18 Behavioral Implicit Communication (BIC): Communicating with Smart Environments via our Practical Behavior and Its Traces 2010 55 1 44 0.3694 19 Group Path Formation 2006 58 1 225 0.3685 20 Follow the Silk Road: How Internet Affordances Influence and Transform Crime and Law Enforcement 2017 14 2 75 0.3684 21 Convolutional Neural Network Bootstrapped by Dynamic Segmentation and Stigmergy-Based Encoding for Real-Time Human Activity Recognition in Smart Homes 2023 15 1 8 0.3678 22 Sociobiology vs Socioecology: Consequences of an Unraveling Debate 2017 7 1 876 0.3562 23 Engineering Human Stigmergy 2015 18 1 225 0.3523 24 Cognitive Maps for Indirect Coordination of Intelligent Agents 2015 9 2 301 0.3509 25 Phenotropic and stigmergic webs: the new reach of networks 2011 17 1 876 0.3447 26 Stigmergic behaviour and nodal places in residential areas: Case of post-socialist city Kharkiv in Ukraine 2019 8 1 76 0.3371 27 How to turn an MAS into a graphical causal model 2022 5 1 225 0.3368 28 Towards a Coordination-Centric Architecture Metamodel for Social Web Applications 2014 8 1 225 0.3309 29 Towards a Coordination-Centric Architecture Metamodel for Social Web Applications 2014 8 1 225 0.3309 30 Knowledge Machines 2004 8 1 876 0.2751 31 Machine Vision for Autonomous Vehicles - Potential and Limitations. A Literature Review 2018 1 2 27 0.2709 32 Understanding Collective Intelligence – A Literature Review from an Engineering Perspective 2016 1 2 27 0.2519 This ranking revealed that citing agents who strategically followed established pheromone trails (cited older and more conceptual works) achieved higher composite scores, providing empirical support for the hypothesis that such trace-based communication enhances environmental impact and scholarly fitness. The top-ranked citing agent, 'A Stigmergy-Based Analysis of City Hotspots to Discover Trends and Anomalies in Urban Transportation Usage' (Alfeo et al. 2018a), achieved the highest fitness score (0.6097) by engaging with three foundational pheromone trails, including one self-citation, with a combined concentration of 972 citations. This demonstrated how strategic indirect coordination with established theoretical pathways enables citing agents to enhance both methodological rigor and environmental impact. Similarly, 'Bacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria' (Gloag et al. 2015) ranked second (0.5942) by coordinating with the highest-concentration pheromone trails in the field (combined concentration of 1160 citations). This illustrated how grounding interdisciplinary research in established pathways strengthens theoretical foundations and enables novel environmental modifications across biological and social domains. The third ranking also uncovered a temporal dimension to strategic pheromone-following. Newer papers such as ‘Cooperation and Deception Through Stigmergic Interactions’ by Bassanetti et al. (2023) (ranked fifth), ‘Cultural-Historical Perspectives on Collective Intelligence’ (Bastandasa-Boada et al. 2021) (ranked fourth) and ‘General Theory of Stigmergy’ (Dipple et al. 2014) (ranked third) benefited disproportionately from citing older, high-impact works. This pattern suggested that (i) foundational traces retain their coordinating power across generations, allowing contemporary researchers to build upon enduring intellectual pathways and (ii) strategic citations of foundational works provide them with credibility and influence. However, the table also revealed exceptions, such as ‘Sleep Behavior Assessment Via Smartwatch and Stigmergic Receptive Fields’ by Alfeo et al. (2018). Despite its high citation counts (ranked sixth), it scored lower in normalized fitness due to limited engagement with theoretical works beyond self-citation behavior. This contrast underscored that sheer visibility does not equate to scholarly fitness; rather, strategic alignment with influential traces is critical. Discussion This research differs from traditional bibliometric (Calof et al. 2022; Min et al. 2021) and sociological approaches (Phelps et al. 2012; Prpić 1996) by focusing on indirect coordination and emergent scholarly behaviors. Unlike conventional studies that examine static organizational structures, this approach discloses (i) trace-based communication, (ii) pathway persistence, and (iii) strategic coordination behaviors that remain invisible in traditional citation analyses, providing a more granular, process-oriented understanding of how intellectual pathways form through autonomous scholarly decisions. Empirical evidence supports the first hypothesis that theoretical papers create stronger, more persistent pheromone trails than applied studies. Citation analysis revealed that five of the top seven most influential papers were both older and conceptual (Table 1). This persistence occurs because theoretical foundations address universal coordination principles rather than technology-specific solutions, demonstrating how academic environments naturally select for contributions with broader applicability. The normalized frequency analysis (Table 2) reinforced the first hypothesis by exposing important distinctions between broad academic visibility and concentrated pathway reinforcement within specialized research communities. It showed that successful academic traces must balance field-specific depth with broad relevance. The analysis demonstrated indirect coordination mechanisms where citing agents enhanced scholarly fitness through selective pathway navigation. The second hypothesis, regarding strategic pheromone-following behavior, received equally empirical support through composite scoring analysis. Citing agents who engaged with multiple high-concentration theoretical trails consistently achieved higher fitness scores (Table 3). This validates the stigmergic principle that successful coordination requires strategic selection of traces with demonstrated persistence and field-specific relevance. Beyond academic contexts, these findings offer insights for organizing collective intelligence to tackle complex adaptive challenges. Digital humanities platforms (Livingstone 2016), collaborative learning environments (Elliot 2016), and decentralized innovation networks (Dounas et al. 2022) could leverage stigmergic principles to create responsive systems that adapt to emergent usage patterns. Several critical areas warrant further investigation. Future research should develop more advanced metrics that capture the full spectrum of academic pheromone trails, including social media engagement and collaborative platform interactions (Wood & Thompson 2021), while conducting longitudinal studies to track pathway persistence mechanisms (White et al. 2020). The dominance of English-language publications highlights the need for comprehensive multilingual analyses incorporating non-Western academic traditions. In addition, experimental validation through controlled studies (Birnbrauer 1981) of researcher citation behavior and computational modeling of academic stigmergy (Marsh & Onof 2008) would strengthen the theoretical framework while informing practical applications for research coordination and knowledge transfer. Also, the implications of self-citations as a trace-based communication mechanism for advancing collective intelligence require further scrutiny. Finally, mapping network relationship strengths, including factors like institutional affiliation and publication context, could offer a nuanced understanding of how intellectual pheromones are adopted by agents and the extent to which their actions are autonomous. This study contains several important limitations that should be considered when interpreting findings. The restriction to the exact term ‘human stigmergy’ may have excluded relevant research using alternative terminologies, creating an incomplete map of the research landscape. The sample size of 93 papers from 1,289 initial entries may not capture the full complexity of the field. The predominance of English-language publications (80%) suggests potential linguistic bias despite multilingual search efforts. In addition, the self-referential nature of analyzing human stigmergy research through stigmergic principles may introduce interpretive circularity that could influence findings. Conclusion This investigation contributes to establish human stigmergy as a coordination mechanism with theoretical foundations and expanding practical applications, providing evidence that this mechanism transcends biological contexts to govern complex human coordination systems. 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Social Science Computer Review , 34 (4), 497-508. https://journals.sagepub.com/doi/full/10.1177/0894439315591136?casa_token=cOcwTaVSUNgAAAAA%3A58zmnE_Czt63EtsH1AkPo7tyIdL4LzMvsVqCgvIqlfmDxZVd0Kah8Atx45VASm3WHWVqxzZalM7v Marsh, L., & Onof, C. (2008). Stigmergic epistemology, stigmergic cognition. Cognitive Systems Research , 9 (1-2), 136-149. https://www.sciencedirect.com/science/article/abs/pii/S1389041707000290 Min, C., Chen, Q., Yan, E., Bu, Y., & Sun, J. (2021). Citation cascade and the evolution of topic relevance. Journal of the Association for Information Science and Technology , 72 (1), 110-127. https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24370?casa_token=tzs5gf0rMHQAAAAA%3AS9abY9UwMSku_BviWO86cTZCouhyKIYBZtp-t-xG_r8BhS9FmIzWHTDtlN8DHRNhZupoh2HAchxfgwA Parunak, H. V. D. (2005). A survey of environments and mechanisms for human-human stigmergy. In Environments for multi-agent systems II (pp. 163–186). Springer. https://doi.org/10.1007/11678809_10 Phelps, C., Heidl, R., & Wadhwa, A. (2012). Knowledge, networks, and knowledge networks: A review and research agenda. Journal of management , 38 (4), 1115-1166. https://journals.sagepub.com/doi/full/10.1177/0149206311432640?casa_token=8Atq6FtH3_YAAAAA%3AvbqeVCPQONMuEA1Ojrf44am-7Nq8wrFCZ2aWT0doqASu3et9-sBfMxyX4K8FNOWdF_hxB4DO2XXY Prpić, K. (1996). Characteristics and determinants of eminent scientists' productivity. Scientometrics , 36 (2), 185-206. https://akjournals.com/view/journals/11192/36/2/article-p185.xml Qiu, J., Zuo, M., Wang, J., & Cai, C. (2021). Knowledge order in an online knowledge community: Group heterogeneity and two paths mediated by group interaction. Journal of the Association for Information Science and Technology, 72 (12), 1495–1508. https://doi.org/10.1002/asi.24523 Rovira, C., Codina, L., & Lopezosa, C. (2021). Language bias in the Google Scholar ranking algorithm. Future internet , 13 (2), 31. https://www.mdpi.com/1999-5903/13/2/31 Schippers, M. C., Ioannidis, J. P., & Luijks, M. W. (2024). Is society caught up in a Death Spiral? Modeling societal demise and its reversal. Frontiers in Sociology , 9 , 1194597. https://www.frontiersin.org/journals/sociology/articles/10.3389/fsoc.2024.1194597/full Theraulaz, G., & Bonabeau, E. (1999). A brief history of stigmergy. Artificial Life, 5 (2), 97–116. https://doi.org/10.1162/106454699568700 White, L. A., VandeWoude, S., & Craft, M. E. (2020). A mechanistic, stigmergy model of territory formation in solitary animals: Territorial behavior can dampen disease prevalence but increase persistence. PLoS computational biology , 16 (6), e1007457. https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007457 Wood, M. A., & Thompson, C. (2021). Crime prevention, swarm intelligence and stigmergy: Understanding the mechanisms of social media-facilitated community crime prevention. The British journal of criminology , 61 (2), 414-433. https://academic.oup.com/bjc/article-abstract/61/2/414/5935390 Zhao, Y., Chen, P., & Kong, X. (2021). Progress and reflection of geographies of consumption from the perspective of new materialism. Progress in Geography, 40 (8), 1382–1393. Endnotes This study reviewed all papers listed to ensure equitable citation opportunities for all relevant research. This is important because Google Scholar's ranking algorithm prioritizes papers based on citation count (Beel & Gipp 2009), author prominence, publication venue prestige, and recency, which can inadvertently create a bias toward well-established researchers and high-impact journals while potentially overlooking valuable contributions from emerging scholars or specialized publications. By reviewing a comprehensive range of search results rather than relying solely on the algorithm's initial rankings, this study could identify diverse perspectives, methodological approaches, and theoretical frameworks that might otherwise be marginalized. This multilingual search of the term ‘human stigmergy’ in different languages was necessary as Rovira et al. (2021) identified a significant bias in Google Scholar’s algorithm, where documents in languages other than English are disproportionately ranked lower in multilingual searches (by year, author, or keywords with identical spelling across languages). Agents directly alter the physical environment to influence subsequent actions, like termites building a nest by adding material. Quantitative stigmergy is about one signal that varies in strength. Qualitative stigmergy is about picking from a set of distinct signals. Self-citation reflects human stigmergy as researchers deposit intellectual ‘pheromones’ through their publications, creating pathways that guide future investigations and maintain conceptual coherence within their work. However, excessive self-citation risks creating circularity in stigmergic systems, where closed loops of knowledge reinforcement limit exposure to diverse perspectives and can lead to echo chambers that constrain rather than facilitate adaptive knowledge exploration (Schippers et al. 2024). self-citations. self-citations. self-citation. Avvenuti et al. (2013:12228-12231) provide formal mathematical definitions for mark creation, decay, and similarity assessment, which are central to the stigmergic process. This conceptual framework is then applied to process motion data in a distributed manner. Graphs Graphs 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files G1.png Graph 1: Language Distribution of Human Stigmergy Publications Included Graph 1: The chart shows that English dominates (80%) human stigmergy publications, followed by French (15%), Spanish (3%), and Portuguese (3%). G2.png Graph 2: Relevance of Main Finding to Human Stigmergy based on Categories Graph 2: Collective Intelligence and Social Systems showed the strongest relevance, emphasizing human stigmergy in decentralization coordination through platforms like wikis and blockchain utilizing digital cues. Interdisciplinary and Human-Centric Studies are highly relevant, with stigmergy driving human coordination in cognitive cities and digital humanities. Computer Science and AI are significant, modeling human behavior via stigmergy in multi-agent systems through self-organization, though less human-focused. Urban and Transportation Systems moderately apply stigmergy to collective mobility through path formation, with limited cognitive ties. Biology and Behavioral Ecology have the least relevance, focusing on non-human systems where human stigmergy serves as an analogy for emergence patterns. G3.png Graph 3: CASP’s Appraisal Graph 3: The chart highlights strong performance in areas like clarity of the research question, selection of relevant papers, quality assessment, and comprehensive outcome reporting. However, it reveals relative weaknesses in study inclusion, precision, and the evaluation of benefits versus harms, suggesting opportunities for enhanced self-organization in quality assessment processes. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7153879","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":587450099,"identity":"2efa12c9-b144-4b86-a0b7-387814cd078b","order_by":0,"name":"Marvin Starominski-Uehara","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYHACNhAhB2Y+ABEHiNRizAMiE0jRkthDtBbdGcnHHvzcY5e+n7077UFCBYMc340E/FrMbqSlG/Y8S87t4Tm73SDhDIOxJGEtOWYSPAeYc3skcrdJJLYxJG4grCX/m+SfA/XpPPJvgVr+MdQToSWHTZrnwOEEHgleoJYGhgQDglrOPDOTljlw3LDnTC7QL8ckDGeeeUBAy/HkZ5JvDlTLs7ef3fbgQ42NPN9xArYgA1AESRCvHKZlFIyCUTAKRgEmAABMrEfECmDhMwAAAABJRU5ErkJggg==","orcid":"","institution":"Temple University, Japan","correspondingAuthor":true,"prefix":"","firstName":"Marvin","middleName":"","lastName":"Starominski-Uehara","suffix":""}],"badges":[],"createdAt":"2025-07-18 04:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7153879/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7153879/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102241069,"identity":"9695a70a-e99b-491e-8ab5-507ee8a986ec","added_by":"auto","created_at":"2026-02-09 16:57:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":185156,"visible":true,"origin":"","legend":"\u003cp\u003eImage 1: PRISMA Flow Diagram\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7153879/v1/12ca4ac80bacfc04be89c742.png"},{"id":103318835,"identity":"acb1fd2e-0389-4531-af4c-694bf6e0e422","added_by":"auto","created_at":"2026-02-24 11:26:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":841905,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7153879/v1/ddc48255-5ab1-4e4b-9659-f736d6fa928b.pdf"},{"id":102241091,"identity":"7a5a7c49-3ba1-4741-871b-d623f1097948","added_by":"auto","created_at":"2026-02-09 16:57:22","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":56722,"visible":true,"origin":"","legend":"\u003cp\u003eGraph 1: Language Distribution of Human Stigmergy Publications Included\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eGraph 1: The chart shows that English dominates (80%) human stigmergy publications, followed by French (15%), Spanish (3%), and Portuguese (3%).\u003c/p\u003e","description":"","filename":"G1.png","url":"https://assets-eu.researchsquare.com/files/rs-7153879/v1/a8619e29ff119ea190b94776.png"},{"id":102241085,"identity":"ec06c154-83e0-420a-8998-cea3e39eb65b","added_by":"auto","created_at":"2026-02-09 16:57:20","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":136837,"visible":true,"origin":"","legend":"\u003cp\u003eGraph 2: Relevance of Main Finding to Human Stigmergy based on Categories\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eGraph 2: Collective Intelligence and Social Systems showed the strongest relevance, emphasizing human stigmergy in decentralization coordination through platforms like wikis and blockchain utilizing digital cues. Interdisciplinary and Human-Centric Studies are highly relevant, with stigmergy driving human coordination in cognitive cities and digital humanities. Computer Science and AI are significant, modeling human behavior via stigmergy in multi-agent systems through self-organization, though less human-focused. Urban and Transportation Systems moderately apply stigmergy to collective mobility through path formation, with limited cognitive ties. Biology and Behavioral Ecology have the least relevance, focusing on non-human systems where human stigmergy serves as an analogy for emergence patterns.\u003c/p\u003e","description":"","filename":"G2.png","url":"https://assets-eu.researchsquare.com/files/rs-7153879/v1/195f4a048cc701f6f2dd045a.png"},{"id":102241080,"identity":"91e2ef68-cb46-42df-98db-2b6c27f7edd3","added_by":"auto","created_at":"2026-02-09 16:57:19","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":160893,"visible":true,"origin":"","legend":"\u003cp\u003eGraph 3: CASP’s Appraisal\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eGraph 3: The chart highlights strong performance in areas like clarity of the research question, selection of relevant papers, quality assessment, and comprehensive outcome reporting. However, it reveals relative weaknesses in study inclusion, precision, and the evaluation of benefits versus harms, suggesting opportunities for enhanced self-organization in quality assessment processes.\u003c/p\u003e","description":"","filename":"G3.png","url":"https://assets-eu.researchsquare.com/files/rs-7153879/v1/257fe95b823480bd900d784a.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stigmergy Facilitates Emergent Patterns in Academic Communication","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eTheoretical papers create stronger, more persistent citation pathways than applied studies\u003c/li\u003e\n \u003cli\u003eCiting influential theoretical works enhances researchers\u0026apos; scholarly impact and fitness\u003c/li\u003e\n \u003cli\u003eDecentralized citation behaviors drive coherent research directions through invisible synchrony\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eJust as termites construct complex mounds through individual actions that modify their environment (Grass\u0026eacute; 1959), academic researchers function as autonomous agents leaving intellectual \u0026apos;pheromones\u0026apos; in digital scholarly environments through their publications. The originality of this approach lies in recognizing that academic papers themselves serve as stigmergic traces -- environmental modifications that facilitate trace-based communication across temporal and spatial boundaries. When Pierre-Paul Grass\u0026eacute; published the theory of stigmergy in 1959, he was not merely documenting a biological phenomenon; the French zoologist was sharing a cue in the academic environment that would guide himself and subsequent researchers toward productive research territories. Grass\u0026eacute;\u0026rsquo;s (1959) foundational paper, with 1907 citations, is evidence of its stigmergic potency and path formation influence.\u003c/p\u003e\n\u003cp\u003eIn the framework of this study, citing researchers function as foraging agents within collaborative networks, actively seeking information traces to meet their immediate scholarly goals. These agents encounter existing papers -- the pheromone trails left by themselves or previous researchers -- and make autonomous decisions about whether to follow, reinforce, or ignore these traces based on their relevance to current objectives. The act of citation represents social signaling and pheromone reinforcement, strengthening certain pathways in the knowledge landscape while allowing others to decay through neglect.\u003c/p\u003e\n\u003cp\u003eThis process exhibits stigmergic characteristics of self-organization: individual researchers operate autonomously without direct coordination, yet their collective citing behaviors create emergent patterns that guide the field\u0026apos;s development. Papers like \u0026apos;A Brief History of Stigmergy\u0026apos; (1999, 876 citations) by Guy Theraulaz and Eric Bonabeau, H. Van Dyke Parunak\u0026apos;s \u0026apos;Survey of Environments and Mechanisms for Human-Human Stigmergy\u0026apos; (2005, 225 citations) and \u0026lsquo;Stigmergy as a Universal Coordination Mechanism: Components, Varieties and Applications\u0026rsquo; by Francis Heylighen (2015, 76 citations)\u0026nbsp;\u0026nbsp;function as major thoroughfares in this intellectual landscape, demonstrating how decentralization in scholarly activity produces coherent directional flows.\u003c/p\u003e\n\u003cp\u003eThis investigation addresses two interconnected research questions: (i) Which academic traces (papers) have created the most influential pheromone pathways in human stigmergy research, as evidenced by sustained citation reinforcement and path formation? (ii) How does strategic pheromone-following behavior (citing influential foundational works) enhance the environmental impact and scholarly fitness of citing agents through indirect coordination mechanisms?\u003c/p\u003e\n\u003cp\u003eThese questions recognize that not all academic traces possess equal stigmergic potential. Some papers, particularly foundational theoretical works, create persistent, high-concentration pheromone trails that continue attracting researchers across multiple generations through sustained trace-based communication, while others represent weak or ephemeral cues that fail to coordinate significant collective behavior.\u003c/p\u003e\n\u003cp\u003eAs for hypotheses, they reflect stigmergic principles governing trace persistence and agent coordination: (i) Foundational theoretical papers create stronger, more persistent pheromone trails than applied studies, evidenced by sustained citation reinforcement over time, as these works address fundamental coordination mechanisms rather than specific applications; (ii) Researchers who strategically follow established pheromone trails (cite foundational works) produce more impactful environmental modifications (higher-quality, more-cited papers), as they build upon proven collaborative networks rather than creating isolated traces.\u003c/p\u003e\n\u003cp\u003eThis stigmergic analysis of human stigmergy research also represents a methodological innovation that transcends traditional bibliometric approaches. By examining a dataset of 93 papers, it demonstrates how autonomous scholarly agents have collectively constructed a knowledge \u0026apos;nest\u0026apos; spanning collective intelligence, computer science, urban planning, and digital humanities through self-organization and emergence.\u003c/p\u003e\n\u003cp\u003eThis investigation yields conceptual lessons demonstrating that \u003cem\u003einvisible synchrony\u003c/em\u003e governs scholarly knowledge construction, where individual researcher decisions aggregate into coherent disciplinary directions through trace-based communication. For the scientific community, this reveals how decentralization can enhance knowledge advancement, suggesting and strengthening models for research coordination that leverage cues and social signaling.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA systematic literature search was conducted using Google Scholar\u003csup\u003ei\u003c/sup\u003e with the exact term \u0026lsquo;human stigmergy\u0026rsquo; to maintain specificity and avoid diluting results with tangentially related research. The search was performed in May 2025 to capture the most recent publications. To ensure comprehensive coverage, the search was extended to eight additional languages: Portuguese, French, Spanish, Italian, Japanese, Chinese, Swedish, and German, yielding a total of 1,289 initial entries across all languages\u003csup\u003eii\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003ePapers were included if they: (i) explicitly addressed \u0026lsquo;stigmergy\u0026rsquo; in the title, abstract, or keywords; (ii) were published in peer-reviewed journals, conference proceedings, or reputable grey literature; (iii) had at least one citation to ensure minimum academic engagement; and (iv) were available in full text. Papers were excluded if they: (i) lacked clear focus on human stigmergy; (ii) were from non-academic sources; (iii) had zero citations indicating absence of social signaling; or (iv) were inaccessible in full text.\u003c/p\u003e\n\u003cp\u003eFollowing PRISMA guidelines (see Image 1), the initial pool of 1,289 entries was systematically screened, resulting in 93 papers meeting the inclusion criteria. Six papers were deemed \u0026lsquo;partially related\u0026rsquo; to human stigmergy but included due to their foundational importance, such as Theraulaz and Bonabeau\u0026apos;s \u0026lsquo;A Brief History of Stigmergy\u0026rsquo; (1999).\u003c/p\u003e\n\u003cp\u003eEach paper was systematically analyzed to extract: (i) publication metadata (author, year, language, publisher); (ii) citation patterns within the corpus; (iii) theoretical versus applied focus; and (iv) disciplinary categorization (See Graph 2). Papers were classified as either theoretical (establishing frameworks, principles, or taxonomies) or applied (implementing stigmergic concepts in specific domains or technologies).\u003c/p\u003e\n\u003cp\u003eThis study introduces a three-tier ranking methodology (see \u0026apos;Results\u0026apos;) to systematically evaluate pheromone pathway formation and scholarly fitness enhancement, progressively refining the analysis from broad citation patterns to specialized field-specific coordination behaviors.\u003c/p\u003e\n\u003cp\u003eThe analysis incorporated the following validation measures to ensure methodological rigor: (i) quality assessment was performed using a customized tool adapted from the Critical Appraisal Skills Program (CASP) (See Graph 3); (ii) the composite scoring methodology balanced recent contributions against established works to mitigate temporal bias; (iii) the 93 papers represented multiple languages, indicating reasonable geographic and linguistic diversity; and (iv) the corpus included both foundational theoretical works and practical applications, enabling comparative analysis of pathway formation patterns across different research approaches.\u003c/p\u003e\n\u003cdiv id=\"edn2\"\u003e\u003cbr\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eFirst Ranking: Identifying the Strongest Pheromone Pathways\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo objectively address the first research question regarding which academic traces have created the most influential pheromone pathways, this study rephrased the inquiry as: \u0026apos;Which papers function as the strongest pheromone trails through sustained cross-citation reinforcement within human stigmergy research via trace-based communication?\u0026apos; This reformulation allowed assessment of which selected academic traces contributed most significantly to distributed knowledge construction. All citations from the final 93 selected papers were collected and tabulated as evidence of pheromone-following behavior. After checking for cross-referencing patterns, this total was reduced to 17 papers representing the most concentrated \u0026lsquo;pheromone\u0026rsquo; trails.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1: Ranking of Cross-Cited Human Stigmergy Papers\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"525\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaper Title\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitation Count\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOlder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMore Conceptual\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eA Brief History of Stigmergy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e1999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eA Survey of Environments and Mechanisms for Human-Human Stigmergy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eStigmergy as a Universal Coordination Mechanism: components, varieties and applications\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eSleep behavior assessment via smartwatch and stigmergic receptive fields\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eSelf-Organized Trail Systems in Groups of Humans\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eGroup Path Formation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eSilent Agents: From Observation to Tacit Communication\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eMARS, a Multi-Agent System for Assessing Rowers\u0026apos; Coordination: Coordination via Motion-Based Stigmergy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eGeneral Theory of Stigmergy: Modelling Stigma Semantics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eBacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eCultural-Historical Perspectives on Collective Intelligence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eImproving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eMulti-Agent Cooperation Using the Ant Algorithm with Variable Pheromone Placement\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eEngineering Human Stigmergy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003ePhenotropic and stigmergic webs: the new reach of networks\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eCognitive Maps for Indirect Coordination of Intelligent Agents\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eOnline Activity Recognition Combining Dynamic Segmentation and Emergent Modeling\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe analysis revealed that foundational theoretical papers create stronger, more persistent pheromone trails than applied studies, as evidenced by sustained citation reinforcement over time through trace-based communication. The most influential pheromone pathway was created by \u0026apos;A Brief History of Stigmergy\u0026apos; (Theraulaz \u0026amp; Bonabeau 1999, 876 citations), which helped establish stigmergy\u0026apos;s fundamental theoretical framework by explaining indirect coordination mechanisms in social insects through environmental traces such as pheromones and nest structures, while suggesting broader applications to human systems including trail formation and collaborative construction through self-organization. This academic trace functions as a major \u0026lsquo;trace\u0026rsquo; in the intellectual landscape, continuously attracting foraging researchers through its high-concentration digital cues.\u003c/p\u003e\n\u003cp\u003eThe second-strongest pathway, \u0026apos;A Survey of Environments and Mechanisms for Human-Human Stigmergy\u0026apos; (Van Dyke Parunak 2005:3, 225 citations), reinforces the pattern by providing a taxonomy of stigmergic interactions specifically within human contexts, systematically distinguishing between marker-based: \u0026lsquo;special markers that agents deposit in the environment\u0026rsquo; versus sematectonic\u003ca href=\"#_edn1\" name=\"_ednref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003eiii\u003c/sup\u003e stigmergy: \u0026lsquo;whether agents base their actions on the current state of the solution\u0026rsquo; and quantitative\u003ca href=\"#_edn2\" name=\"_ednref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003eiv\u003c/sup\u003e (\u0026lsquo;whether the signals are a single scalar analogous to a potential field\u0026rsquo;) versus qualitative\u003ca href=\"#_edn3\" name=\"_ednref3\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003ev\u003c/sup\u003e variations (\u0026lsquo;whether they form a set of discrete options\u0026rsquo;) via trace-based communication. These interactions demonstrate how specialized theoretical contributions can create persistent pathways through trace-based communication in specific research territories using digital cues.\u003c/p\u003e\n\u003cp\u003eThe third-ranked paper, \u0026apos;Stigmergy as a Universal Coordination Mechanism\u0026apos; (2015, 76 citations), further validates the pathway-forming capacity of theoretical contributions by offering a framework that positions stigmergy as a coordination mechanism enabling complex organization across human and non-human domains. This work specifically addresses human cognition through external memory systems and collaborative platforms like Wikipedia, showing how stigmergic principles scale to digital environments.\u003c/p\u003e\n\u003cp\u003eExamining the complete ranking revealed that five of the top seven papers are both older (published before 2010) and conceptual in nature, collectively accounting for 1,262 citations out of the total 1,649 citations across all ranked papers -- representing 77% of the total pheromone concentration through emergence patterns. In contrast, newer applied studies, such as smartwatch-based sleep behavior assessment (rank 4) and computational approaches to activity recognition (rank 17), while technically innovative, have achieved relatively modest citation counts despite their practical applications, indicating weaker path formation capabilities.\u003c/p\u003e\n\u003cp\u003eThis pheromone distribution pattern confirms that theoretical contributions establishing core principles, frameworks, and taxonomies of human stigmergy create substantial and persistent pathways through environmental trace deposition via cues, with foundational works continuing to attract foraging researchers and influence contemporary research directions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSecond Ranking: Normalizing Pathway Strength by Field-Specific Reinforcement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe second ranking refined pathway analysis by examining how frequently each of the 93 selected papers engaged in cross-citation behavior -- self-citation\u003ca href=\"#_edn4\" name=\"_ednref4\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003evi\u003c/sup\u003e was only marginally observed in this dataset -- as evidence of pheromone-following within the specific research environment. This frequency (\u0026apos;Appearances\u0026apos;) was normalized with total citation counts to re-rank the remaining 17 papers, revealing the distinction between broad academic impact and concentrated path formation within the human stigmergy research ecosystem through self-organization.\u003c/p\u003e\n\u003cp\u003eTable 2: Ranking of Cross-Cited Human Stigmergy Papers Normalized by Frequency\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaper Title\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAppearances\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNorm. Citation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNorm. Appearances\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCombined Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eA Brief History of Stigmergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eA Survey of Environments and Mechanisms for Human-Human Stigmergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.2517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.5009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eStigmergy as a Universal Coordination Mechanism: components, varieties and applications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.1667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.1227\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMARS, a Multi-Agent System for Assessing Rowers\u0026apos; Coordination: Coordination via Motion-Based Stigmergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.1667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.1007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eGroup Path Formation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0706\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eGeneral Theory of Stigmergy: Modelling Stigma Semantics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eCultural-Historical Perspectives on Collective Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eImproving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0544\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eEngineering Human Stigmergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003ca href=\"#_edn5\" name=\"_ednref5\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003evii\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0474\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eCognitive Maps for Indirect Coordination of Intelligent Agents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003ca href=\"#_edn6\" name=\"_ednref6\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003eviii\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eSleep behavior assessment via smartwatch and stigmergic receptive fields\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003csup\u003eix\u003c/sup\u003e\u003ca href=\"#_edn7\" name=\"_ednref7\" title=\"\"\u003e\u003c/a\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0335\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eSelf-organized Trail Systems in Groups of Humans\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0295\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eSilent Agents: From Observation to Tacit Communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eBacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMulti-Agent Cooperation Using the Ant Algorithm with Variable Pheromone Placement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePhenotropic and stigmergic webs: the new reach of networks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.0052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eOnline Activity Recognition Combining Dynamic Segmentation and Emergent Modeling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe normalized frequency analysis exposed shifts that provide nuanced insights into pheromone pathway formation. While foundational theoretical traces maintained dominance, the analysis revealed distinctions between broader academic visibility and concentrated pathway reinforcement within the human stigmergy research community.\u003c/p\u003e\n\u003cp\u003e\u0026apos;A Brief History of Stigmergy\u0026apos; (Theraulaz \u0026amp; Bonabeau 1999) maintained its position through both pheromone concentration (876 citations) and frequent reinforcement by foraging agents (13 appearances) via social signaling. This trace\u0026apos;s sustained influence demonstrates how foundational environmental modifications continue to coordinate research behavior across multiple scholar generations through persistent high-concentration pathways and emergence patterns.\u003c/p\u003e\n\u003cp\u003e\u0026apos;A Survey of Environments and Mechanisms for Human-Human Stigmergy\u0026apos; (Van Dyke Parunak 2005) strengthened its position with a combined score of 0.5009, appearing as a reference point for 10 out of 93 papers through collaborative networks. This enhanced ranking reflected the work\u0026apos;s critical role as a coordination mechanism, bridging biological stigmergy concepts to human contexts through systematic taxonomies that enable indirect coordination among researchers via digital cues.\u003c/p\u003e\n\u003cp\u003eThe normalized analysis, however, revealed distinct patterns in how theoretical versus applied traces function within the stigmergic research environment. Applied studies such as \u0026apos;Sleep Behavior Assessment Via Smartwatch and Stigmergic Receptive Fields\u0026apos; (Alfeo et al. 2018) (dropped from 4th to 11th) and \u0026apos;Self-Organized Trail Systems in Groups of Humans\u0026apos; (Goldstone \u0026amp; Roberts 2006) (dropped from 5th to 12th) suggesting that substantial pheromone concentrations do not necessarily translate into sustained pathway reinforcement within the specialized field through trace-based communication.\u003c/p\u003e\n\u003cp\u003eConversely, newer theoretical traces like \u0026apos;MARS, a Multi-Agent System for Assessing Rowers\u0026apos; Coordination\u0026apos; (Avvenuti et al. 2013) rose from 8th to 4th position, suggesting that theoretical contributions\u003ca href=\"#_edn8\" name=\"_ednref8\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003ex\u003c/sup\u003e with direct human stigmergy applications maintain stronger coordination functions as demonstrated by the MARS system, which uses motion-based stigmergy to assess rowing asynchrony in a shared sensing space.\u003c/p\u003e\n\u003cp\u003eThe most significant insight concerns highly cited but less field-relevant studies. Papers focusing on computational applications of stigmergic principles to human behavioral data, while achieving substantial citation counts, experienced dramatic ranking drops when field-specific cross-referencing was considered. This pattern indicated that technical implementations, though academically successful, may not directly advance theoretical understanding of interdisciplinary human stigmergy mechanisms.\u003c/p\u003e\n\u003cp\u003eThe refined ranking provided stronger empirical support for the principle that theoretical traces create more persistent and concentrated pheromone pathways in human stigmergy research. Top-ranking environmental modifications consistently focus on foundational frameworks -- from Theraulaz and Bonabeau\u0026apos;s (1999) biological principles to Van Dyke Parunak\u0026apos;s (2005) human-specific taxonomies and Heylighen\u0026apos;s (2015) universal coordination mechanisms -- rather than specific technical applications. This demonstrated that conceptual contributions maintain their coordination capacity within the specialized research community, serving as essential navigation points that shape ongoing theoretical development and empirical investigation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThird Ranking: Analyzing Strategic Pheromone-Following Behavior and Scholarly Fitness\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe third ranking addressed the second research question regarding how strategic pheromone-following behavior enhances the environmental impact and scholarly fitness of citing agents through indirect coordination mechanisms. This analysis examined how researchers functioning as foraging agents can improve their own environmental modifications (paper quality and citation impact) by strategically following established pheromone trails (citing influential foundational works).\u003c/p\u003e\n\u003cp\u003eThe 32 papers selected for this assessment represent citing agents that engaged in cross-referencing (including self-citation) behavior at least once among the 93 selected papers, demonstrating active pheromone-following within the research environment through trace-based communication. A composite scoring method, designed to objectively assess fitness enhancement via strategic coordination, was developed by incorporating four equally weighted components: Year Published, Total Number of Citations, Number of Citations by Human Stigmergy Articles, and the Sum of Citations of Cited Human Stigmergy Articles.\u003c/p\u003e\n\u003cp\u003eTable 3: Ranking of Citing Papers Normalized by Year Published, Total Citations, Human Stigmergy Citations, and Sum of Citing Articles\u0026rsquo; Citations\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaper Title\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear Published\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Citations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHuman Stigmergy Citations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSum of Citing Articles\u0026apos; Citations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eA Stigmergy-Based Analysis of City Hotspots to Discover Trends and Anomalies in Urban Transportation Usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.6097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eBacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5942\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eGeneral Theory of Stigmergy: Modelling Stigma Semantics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5847\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eCultural-Historical Perspectives on Collective Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5574\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eCooperation and deception through stigmergic interactions in human groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5408\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eSleep behavior assessment via smartwatch and stigmergic receptive fields\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eStigmergy as a Universal Coordination Mechanism: components, varieties and applications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5236\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eAnt Colonies: Building Complex Organizations with Minuscule Brains and No Leaders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.5151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003ePervasive Pheromone-Based Interaction with RFID Tags\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.4969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eThe inheritance of alternative nest architectural traditions in stingless bees\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.4817\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eJoint action in an elite rowing pair crew after intensive team training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eCan we identify general architectural principles that impact the collective behaviour of both human and animal systems?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.4645\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eMicro-Patterned Surfaces That Exploit Stigmergy to Inhibit Biofilm Expansion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.4456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eImproving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.4349\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eMARS, a Multi-Agent System for Assessing Rowers\u0026apos; Coordination: Coordination via Motion-Based Stigmergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eSelf-Organization Leads to Supraoptimal Performance in Public Transportation Systems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.4263\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eEducation for Collective Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eBehavioral Implicit Communication (BIC): Communicating with Smart Environments via our Practical Behavior and Its Traces\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eGroup Path Formation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3685\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eFollow the Silk Road: How Internet Affordances Influence and Transform Crime and Law Enforcement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3684\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eConvolutional Neural Network Bootstrapped by Dynamic Segmentation and Stigmergy-Based Encoding for Real-Time Human Activity Recognition in Smart Homes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3678\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eSociobiology vs Socioecology: Consequences of an Unraveling Debate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eEngineering Human Stigmergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3523\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eCognitive Maps for Indirect Coordination of Intelligent Agents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3509\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003ePhenotropic and stigmergic webs: the new reach of networks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3447\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eStigmergic behaviour and nodal places in residential areas: Case of post-socialist city Kharkiv in Ukraine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eHow to turn an MAS into a graphical causal model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3368\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eTowards a Coordination-Centric Architecture Metamodel for Social Web Applications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3309\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eTowards a Coordination-Centric Architecture Metamodel for Social Web Applications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.3309\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eKnowledge Machines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.2751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eMachine Vision for Autonomous Vehicles - Potential and Limitations. A Literature Review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.2709\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003eUnderstanding Collective Intelligence \u0026ndash; A Literature Review from an Engineering Perspective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.2519\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThis ranking revealed that citing agents who strategically followed established pheromone trails (cited older and more conceptual works) achieved higher composite scores, providing empirical support for the hypothesis that such trace-based communication enhances environmental impact and scholarly fitness. The top-ranked citing agent, \u0026apos;A Stigmergy-Based Analysis of City Hotspots to Discover Trends and Anomalies in Urban Transportation Usage\u0026apos; (Alfeo et al. 2018a), achieved the highest fitness score (0.6097) by engaging with three foundational pheromone trails, including one self-citation, with a combined concentration of 972 citations. This demonstrated how strategic indirect coordination with established theoretical pathways enables citing agents to enhance both methodological rigor and environmental impact.\u003c/p\u003e\n\u003cp\u003eSimilarly, \u0026apos;Bacterial Stigmergy: An Organising Principle of Multicellular Collective Behaviours of Bacteria\u0026apos; (Gloag et al. 2015) ranked second (0.5942) by coordinating with the highest-concentration pheromone trails in the field (combined concentration of 1160 citations). This illustrated how grounding interdisciplinary research in established pathways strengthens theoretical foundations and enables novel environmental modifications across biological and social domains.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe third ranking also uncovered a temporal dimension to strategic pheromone-following. Newer papers such as \u0026lsquo;Cooperation and Deception Through Stigmergic Interactions\u0026rsquo; by Bassanetti et al. (2023) (ranked fifth), \u0026lsquo;Cultural-Historical Perspectives on Collective Intelligence\u0026rsquo; (Bastandasa-Boada et al. 2021) (ranked fourth) and \u0026lsquo;General Theory of Stigmergy\u0026rsquo; (Dipple et al. 2014) (ranked third) benefited disproportionately from citing older, high-impact works. This pattern suggested that (i) foundational traces retain their coordinating power across generations, allowing contemporary researchers to build upon enduring intellectual pathways and (ii) strategic citations of foundational works provide them with credibility and influence. However, the table also revealed exceptions, such as \u0026lsquo;Sleep Behavior Assessment Via Smartwatch and Stigmergic Receptive Fields\u0026rsquo; by Alfeo et al. (2018). Despite its high citation counts (ranked sixth), it scored lower in normalized fitness due to limited engagement with theoretical works beyond self-citation behavior. This contrast underscored that sheer visibility does not equate to scholarly fitness; rather, strategic alignment with influential traces is critical.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis research differs from traditional bibliometric (Calof et al. 2022; Min et al. 2021) and sociological approaches (Phelps et al. 2012; Prpić 1996) by focusing on indirect coordination and emergent scholarly behaviors. Unlike conventional studies that examine static organizational structures, this approach discloses (i) trace-based communication, (ii) pathway persistence, and (iii) strategic coordination behaviors that remain invisible in traditional citation analyses, providing a more granular, process-oriented understanding of how intellectual pathways form through autonomous scholarly decisions.\u003c/p\u003e\n\u003cp\u003eEmpirical evidence supports the first hypothesis that theoretical papers create stronger, more persistent pheromone trails than applied studies. Citation analysis revealed that five of the top seven most influential papers were both older and conceptual (Table 1). This persistence occurs because theoretical foundations address universal coordination principles rather than technology-specific solutions, demonstrating how academic environments naturally select for contributions with broader applicability.\u003c/p\u003e\n\u003cp\u003eThe normalized frequency analysis (Table 2) reinforced the first hypothesis by exposing important distinctions between broad academic visibility and concentrated pathway reinforcement within specialized research communities. It showed that successful academic traces must balance field-specific depth with broad relevance. The analysis demonstrated indirect coordination mechanisms where citing agents enhanced scholarly fitness through selective pathway navigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe second hypothesis, regarding strategic pheromone-following behavior, received equally empirical support through composite scoring analysis. Citing agents who engaged with multiple high-concentration theoretical trails consistently achieved higher fitness scores (Table 3). This validates the stigmergic principle that successful coordination requires strategic selection of traces with demonstrated persistence and field-specific relevance.\u003c/p\u003e\n\u003cp\u003eBeyond academic contexts, these findings offer insights for organizing collective intelligence to tackle complex adaptive challenges. Digital humanities platforms (Livingstone 2016), collaborative learning environments (Elliot 2016), and decentralized innovation networks (Dounas et al. 2022) could leverage stigmergic principles to create responsive systems that adapt to emergent usage patterns.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeveral critical areas warrant further investigation. Future research should develop more advanced metrics that capture the full spectrum of academic pheromone trails, including social media engagement and collaborative platform interactions (Wood \u0026amp; Thompson 2021), while conducting longitudinal studies to track pathway persistence mechanisms (White et al. 2020). The dominance of English-language publications highlights the need for comprehensive multilingual analyses incorporating non-Western academic traditions. In addition, experimental validation through controlled studies (Birnbrauer 1981) of researcher citation behavior and computational modeling of academic stigmergy (Marsh \u0026amp; Onof 2008) would strengthen the theoretical framework while informing practical applications for research coordination and knowledge transfer. Also, the implications of self-citations as a trace-based communication mechanism for advancing collective intelligence require further scrutiny. Finally, mapping network relationship strengths, including factors like institutional affiliation and publication context, could offer a nuanced understanding of how intellectual pheromones are adopted by agents and the extent to which their actions are autonomous.\u003c/p\u003e\n\u003cp\u003eThis study contains several important limitations that should be considered when interpreting findings. The restriction to the exact term \u0026lsquo;human stigmergy\u0026rsquo; may have excluded relevant research using alternative terminologies, creating an incomplete map of the research landscape. The sample size of 93 papers from 1,289 initial entries may not capture the full complexity of the field. The predominance of English-language publications (80%) suggests potential linguistic bias despite multilingual search efforts. In addition, the self-referential nature of analyzing human stigmergy research through stigmergic principles may introduce interpretive circularity that could influence findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis investigation contributes to establish human stigmergy as a coordination mechanism with theoretical foundations and expanding practical applications, providing evidence that this mechanism transcends biological contexts to govern complex human coordination systems. This understanding opens new possibilities for designing digital environments and collaborative platforms that leverage trace-based communication to enhance collective intelligence and spontaneous alignment of diverse actors toward common, shared goals.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted without financial support from funding agencies or grants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlfeo, A. L., Barsocchi, P., Cimino, M. G. C. A., La Rosa, D., Palumbo, F., \u0026amp; Vaglini, G. (2018). Sleep behavior assessment via smartwatch and stigmergic receptive fields. \u003cem\u003ePersonal and Ubiquitous Computing, 21\u003c/em\u003e(5), 937\u0026ndash;949. https://doi.org/10.1007/s00779-017-1038-9\u003c/li\u003e\n\u003cli\u003eAlfeo, A. L., Cimino, M. G. C., Egidi, S., Lepri, B., \u0026amp; Vaglini, G. (2018a). 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This is important because Google Scholar\u0026apos;s ranking algorithm prioritizes papers based on citation count (Beel \u0026amp; Gipp 2009), author prominence, publication venue prestige, and recency, which can inadvertently create a bias toward well-established researchers and high-impact journals while potentially overlooking valuable contributions from emerging scholars or specialized publications. By reviewing a comprehensive range of search results rather than relying solely on the algorithm\u0026apos;s initial rankings, this study could identify diverse perspectives, methodological approaches, and theoretical frameworks that might otherwise be marginalized.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e This multilingual search of the term \u0026lsquo;human stigmergy\u0026rsquo; in different languages was necessary as Rovira et al. (2021) identified a significant bias in Google Scholar\u0026rsquo;s algorithm, where documents in languages other than English are disproportionately ranked lower in multilingual searches (by year, author, or keywords with identical spelling across languages).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e Agents directly alter the physical environment to influence subsequent actions, like termites building a nest by adding material.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e Quantitative stigmergy is about one signal that varies in strength.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e Qualitative stigmergy is about picking from a set of distinct signals.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e Self-citation reflects human stigmergy as researchers deposit intellectual \u0026lsquo;pheromones\u0026rsquo; through their publications, creating pathways that guide future investigations and maintain conceptual coherence within their work. However, excessive self-citation risks creating circularity in stigmergic systems, where closed loops of knowledge reinforcement limit exposure to diverse perspectives and can lead to echo chambers that constrain rather than facilitate adaptive knowledge exploration (Schippers et al. 2024).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e self-citations.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e self-citations.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e self-citation.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e Avvenuti et al. (2013:12228-12231) provide formal mathematical definitions for mark creation, decay, and similarity assessment, which are central to the stigmergic process. This conceptual framework is then applied to process motion data in a distributed manner.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Graphs","content":"\u003cp\u003eGraphs 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"stigmergy, collective intelligence, indirect coordination, academic knowledge networks, self-organization","lastPublishedDoi":"10.21203/rs.3.rs-7153879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7153879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study applies stigmergic principles to examine human stigmergy research itself, treating academic papers as environmental traces. Through systematic analysis, this investigation reveals how scholars function as autonomous agents depositing intellectual ‘pheromones’ through publications, creating pathways that guide collective knowledge advancement. Using three progressive ranking methodologies, the study demonstrates that foundational theoretical papers create stronger, more persistent pathways than applied studies. The analysis validates that researchers strategically engaging with established theoretical pathways achieve higher scholarly fitness, offering insights for organizing collaborative intelligence systems.","manuscriptTitle":"Stigmergy Facilitates Emergent Patterns in Academic Communication","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 16:56:55","doi":"10.21203/rs.3.rs-7153879/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ff3f404-8881-4c22-9ded-b0f27b71ca31","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62507880,"name":"Biological sciences/Psychology"},{"id":62507881,"name":"Social science/Psychology"},{"id":62507882,"name":"Social science/Science technology and society"}],"tags":[],"updatedAt":"2026-02-24T11:25:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 16:56:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7153879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7153879","identity":"rs-7153879","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}