User Voting Behaviour in reward-based Social Networks

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Abstract Cooperation is essential for addressing large-scale social dilemmas that require coordinated behavioral change. While traditional social media platforms offer valuable insights into cooperative behavior, their unstructured design and limited transparency hinder the systematic study of cooperation dynamics. In contrast, Web3 social platforms provide a novel opportunity to analyze online cooperation, as they embed monetary rewards that are explicitly tied to cooperative actions such as content co-curation. In this work, we study 2.5 years of user interactions on Steemit, a Web3 platform whose reward system inherently reflects a social dilemma. On Steemit both creators and voters of posts are rewarded proportionally to the post popularity, however users have a limited voting budget, encouraging strategic decisions about which content and authors to support through potentially different cooperation strategies. We investigate how individual voting behavior is shaped by both strategic and social factors under the platform's stable, transparent, and endogenous reward rules. We test three key hypotheses on whether cooperation is driven by reciprocity, familiarity with previous partners, or historical power of content creators in attracting high rewards. We find that reciprocity is the primary correlate of voting decisions, while content creator power plays a minimal role. This finding backs research in social psychology suggesting that psycho-social norms can exert a stronger influence on cooperative behavior than rational reward-maximizing strategies. Our study highlights the potential of Web3 platforms as empirical testbeds for cooperation research and offers practical implications for designing digital systems that promote sustained collective action.
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User Voting Behaviour in reward-based Social Networks | 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 Research Article User Voting Behaviour in reward-based Social Networks Alessia Galdeman, Matteo Zignani, Luca Maria Aiello, Sabrina Gaito This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8907613/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Cooperation is essential for addressing large-scale social dilemmas that require coordinated behavioral change. While traditional social media platforms offer valuable insights into cooperative behavior, their unstructured design and limited transparency hinder the systematic study of cooperation dynamics. In contrast, Web3 social platforms provide a novel opportunity to analyze online cooperation, as they embed monetary rewards that are explicitly tied to cooperative actions such as content co-curation. In this work, we study 2.5 years of user interactions on Steemit, a Web3 platform whose reward system inherently reflects a social dilemma. On Steemit both creators and voters of posts are rewarded proportionally to the post popularity, however users have a limited voting budget, encouraging strategic decisions about which content and authors to support through potentially different cooperation strategies. We investigate how individual voting behavior is shaped by both strategic and social factors under the platform's stable, transparent, and endogenous reward rules. We test three key hypotheses on whether cooperation is driven by reciprocity, familiarity with previous partners, or historical power of content creators in attracting high rewards. We find that reciprocity is the primary correlate of voting decisions, while content creator power plays a minimal role. This finding backs research in social psychology suggesting that psycho-social norms can exert a stronger influence on cooperative behavior than rational reward-maximizing strategies. Our study highlights the potential of Web3 platforms as empirical testbeds for cooperation research and offers practical implications for designing digital systems that promote sustained collective action. cooperation blockchain online social networks reward-based systems web3 Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 05 Mar, 2026 Reviewers invited by journal 04 Mar, 2026 Editor assigned by journal 24 Feb, 2026 Submission checks completed at journal 19 Feb, 2026 First submitted to journal 18 Feb, 2026 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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