Psychological characteristics of in-group favoritism in internet altruistic behavior transmission

Psychological characteristics of in-group favoritism in internet altruistic behavior transmission | 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 Psychological characteristics of in-group favoritism in internet altruistic behavior transmission Huiping Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5143264/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 “Pay-it-forward reciprocity” refers to the phenomenon of altruistic behavior being transmitted between strangers when one stranger shows goodwill toward a third party. This study implemented two experiments to explore the characteristics of Internet altruistic behavior transmission (IABT). Experiment 1 (participants: n = 312, college students, mean age = 20.11 years, SD = 1.45) used a specifically-designed situational questionnaire and situational recall tasks to examine whether Internet altruistic behavior (IAB) can be transmitted between strangers. Results showed that the level of IAB in the experimental group was higher compared to that of participants who did not experience IAB from strangers. That is, individuals who received online help from others tended to then help other strangers later on. Experiment 2 (participants: n = 274, college students, mean age = 19.68 years, SD = 1.02) investigated whether an in-group favoritism effect was present in IABT, and revealed that individuals showed a greater degree of IABT toward in-groups than to outgroups. These findings are consistent with the self-classification theory, which says that individuals categorize themselves into different groups based on similarities and differences with others, and are inclined to adopt behaviors that align with the identity of the categorized group, this implies that individuals are more likely to transmit IAB to their in-group. internet altruistic behavior internet altruistic behavior transmission in-group favoritism indirect reciprocity Figures Figure 1 Figure 2 Introduction Altruism is a prosocial behavior performed by a giver within appropriate situational context. It can also involve a multiple individuals over an extended timeframe, thereby forming a continuous benign social interaction (i.e., “transmission of prosocial behaviors”; Desteno et al., 2010 ; Gray et al., 2014 ; Stanca, 2009 ). Interestingly, prosocial behavior can be transmitted interpersonally to involve cooperative behavior between strangers (Kawamichi et al., 2019 ; Okada, 2020 ). Transmitting prosocial behavior seems to operate on reciprocity (Schmid et al., 2021 ), of which the transmission of online prosocial behaviors remains poorly understood. With the rapid development of information technology, the Internet not only provides people with a wide range of information acquisition channels, it has also becomes an important platform for social interaction and cooperation. For instance, this digital age, Internet altruistic behavior (IAB) is becoming an everyday experience more practices and less studied. To clarify the Internet altruistic behavior transmission (IABT), we designed a preliminary experiment and two behavioral experiments to investigate the psychological characteristics of IABT based on network interpersonal interactions. Findings would provide a more comprehensive understanding Internet altruism and interpersonal relationships, and which would provide a basis for theory development and testing regarding this phenomenon in today’s active online community living. Internet altruistic behavior (IAB) is a prosocial behavior that takes place in the Internet situation and does not ask for return (Zheng, 2013 ). The essence IAB is consistent with that of offline or “real-life” altruistic behavior, differing only in the environments in which they occur. This distinction does imbue IAB with specific unique characteristics, however, as the virtual, timeless, and convenient natures of the online realm lend a certain complexity to IAB. IAB comprises four dimensions: online support, online guidance, online sharing, and online reminders. For instance, online support is a supportive behavior given to others on the Internet, such as showing care and encouragement towards online friends, wishing others well, and providing others with positive feedback after reading their posts. Online guidance is the act of providing others with assistance or direction on the Internet, and encompasses activities such as guiding beginners in navigating online spaces or educating them on safeguarding their privacy and personal information online. Online sharing is the act of sharing one’ s own resources to others over the Internet, such as uploading and sharing study materials, or recommending useful articles to others. Finally, online reminders refer to the act of providing prompts or warnings to others on the Internet, for example to exposing illicit activities, informing fellow netizens about online scams, or reporting inappropriate online content. Most of the research on IAB focuses on the psychological characteristics of the individual (Zheng et al., 2021 ; Zhang et al., 2021 ), ignoring the interpersonal interaction situation pattern in the Internet and the experience of the individual in the Internet interaction situation. In particular, there is a lack of research on the internal psychological mechanism of IABT between the two roles (giver and recipient), that is, interpersonal interaction. This has the limitation to open with researchers having focused excessively on the individual characteristics of giver in the online environment, the significance of interpersonal dynamics within the network has been overlooked, along with the emotions and attributes of the recipient within these interpersonal interactions. Consequently, the study of the interaction between the giver and the recipient remains to be investigated. We aim to address this gap in the evidence. Is IAB be transmittable? Reciprocity is the core component in prosocial behavior transmission (Whitham, 2021 ), and this can be direct or indirect. Direct reciprocity is the exchange of altruistic behaviors between two individuals, which can result in mutually beneficial outcomes, while indirect reciprocity is when one provides assistance to another which, while it does not result in direct reciprocation from the recipient, it does lead to reciprocation from others further down the line (Romano et al., 2022 ). IAB is considered a special type of altruism (Schmid et al., 2021 ), in that it is enabled by the unique characteristics of the online context. The specific environment of virtual networks, with their nature of sharing, openness, and anonymity, contribute to the occurrence of IAB and help broaden the audience of potential recipients (Wright & Li, 2011 ). This has been empirically demonstrated real-life situations via a natural experiment conducted on an online platform (Mujcic & Leibbrandt, 2017 ), by which individuals, upon receiving assistance from fellow drivers, were over twice as likely to exhibit similar behavior towards a third party. This observation remained consistent across various factors, including age, gender, social status, presence of onlookers, and the opportunity cost of time. The rapid growth of social media and Internet technology has dramatically increased our potential to interact extensively with strangers online. The high frequency of these online interactions may increase the likelihood of people providing feedback and assistance to one another. These studies provide substantial evidence supporting the wide dissemination of IAB, even among strangers. Therefore, based on the aforementioned empirical findings, this study proposed the first hypothesis: Hypothesis 1 IAB is transitive in unfamiliar groups. The question is: Who is more likely to receive a greater amount of IAB? According to the self-classification theory (Tajfel et al., 1971 ), people tend to classify each other into in-group and outgroup, with a preference for in-groups and devaluation of outgroups (Hornsey, 2008 ). In-group favoritism would show by preference towards those who belong to the social group (Zhang et al., 2021 ), which would also strengthen their reputation among the in-group and elevate their positive standing by sharing resources and engaging in interactions (Essien et al., 2020 ; Iacoviello & Spears, 2018 ; Skoog, 2020 ). This effect may be from a perception of similarity (in this case, similarity in resources) heightening the favoritism which is diminished for outgroups (Nakashima & Flynn 2016 ). Thus, favoritism shows in prosocial behaviors towards those with whom people have a shared social identity (Aksoy 2019 ; Melamed et al., 2020 ; Romano et al., 2021 ; Whitham, 2018). However, people may have differing attitudes and behavioral tendencies towards in-groups versus outgroups of which the contribution to IABT is less known. The aim in the study was to investigate the phenomenon of IAB exhibits transmissibility among unfamiliar individuals and the in-group favoritism in IABT. This study proposed the following hypotheses: Hypothesis 2 IABT is associated with in-group favoritism more, compared the outgroup. The present study To further explore these hypotheses, two experiments were designed. The first experiment investigated whether an individual who received IAB was more likely to transmit IAB in a writing task. The second experiment investigated in-group favoritism among IABT by developing two self-designed scenario questionnaires. Ethics compliance. The students participants were from the Gannan Normal University of Education Science School. This study was conducted in accordance with the principles of the Declaration of Helsinki. Participants individually consented for study. We obtained parental/giardian consent for participants under the age of 18. Participants self-reported their demographics (including gender, average daily online time, etc.). They received a pen as a reward for their participation. Data analysis . We used SPSS (IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.) to analyze data. Experiment 1: The occurrence of Internet altruistic behavior transmission (IABT) among strangers Pre - study Method The purpose of the pre-study was to explore the effectiveness of the text-based materials used to prime recipients for receiving IAB by using a situational recall task. Priming of IABT was done in two ways: either the participant was primed to receive IAB from another individual, or the participant was primed to carry out IAB toward another person. Participants sampling. According to the calculation of G*Power 3.1 software, the statistical test force is 1 − β = 0.95, two-sided test ɑ = 0.05 and effect size d = 0.80, conducting independent sample t -test results showed that the study required at least 84 participants. Thus, we recruited 84 college students through paper questionnaires, including 55 male students (66.3%) and 29 female students (33.8%), ranging in age from 17 to 24 years old. The average online time per day was 6.22 hours. Participants were randomly assigned to one of two groups: accepting IAB group ( n = 42) and not accepting IAB group ( n = 42). Experimental Design . We adopted the between-subjects design. The independent variable was whether or not to accept IAB, with consists of two levels: accepting or not accepting, and the dependent variable was the degree of getting help. Materials and Procedure /Instruction. Each group received specific instructions, as outlined below. Accept IAB group : “Please recall or imagine the work or life experience in which someone committed IAB against you, that is, the experience of someone helping you on a Internet platform”. Describe your personal feelings and experiences under the above experience. Please try to exceed 200 words. Not-accepting IAB group : “Please recall or imagine your experience of communicating with netizens on an interesting topic on the Internet platform”. All participants were required describe in detail (over 200 word). After completing the above writing task, participants responded to a question on “the extent to which you have received the help of the other party and are beneficial to you” (1-7 points). Analysis. We used SPSS (IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.) to conduct an independent sample t -test on the degree of help obtained by the participants in the two cases of receiving and not receiving the IAB from others. Results. Accepting IAB manipulation tests, participants who accepted IAB reported significantly higher feelings of goodwill (M = 6.65, SD = 0.89) compared to those who did not accept (M = 4.00, SD = 1.43), t (82) = 9.93, p < 0.001, Cohen’s d = 2.22. The results of the pre-study revealed that accepting the manipulation of IAB effectively produced the desired effect. This indicated that the selected experimental materials were appropriate. Formal Study Method Participants . As previously reported, according to the calculation of G*Power 3.1 software, the statistical test force is 1 − β = 0.95, two-sided test ɑ = 0.05 and effect size d = 0.80, conducting independent sample t -test results showed that the study required at least 84 participants. We recruited 312 college students (146 male and 166 female), aged from 17 to 24 years (M = 20.11, SD = 1.45), with an average online time of 6.15 hours. Experimental Design We adopted the between-subjects design. The independent variable was IAB acceptance, and the dependent variable was IABT. Materials and Procedure Firstly, we used the same self-designed acceptance scenario materials for IAB and IABT as the pre-study. Participants received an email from a stranger with the subject line “Help!”. The email explained that a foreign psychology graduate student was preparing his / her graduation thesis. His / her research protocol has been approved and recognized by the tutor. However, the current problem was that he/she need search for a large number of participants to complete the relevant online questionnaires. Therefore, the email stated that the student was seeking help online to complete his/her thesis research. Participants could contribute by clicking on the link in the email and filling out the related online questionnaire. Following previous research on help behavior situations online (Wu et al., 2017), participants were asked to rate two items: (1) Are you willing to help him/her? (2) How much time are you willing to spend helping? Responses to both items used a 5-point scale. The total score across these two questions served as the index for IABT. Results The experimental group and the control group . Independent sample t -test analysis was carried out for the experimental group and the control group. The participants’ IAB in the experimental group is significantly higher than that of the control group, that is, IAB is transmitted among the unfamiliar groups of college students. The score of the experimental group on the degree of willingness (M = 3.35, SD = 1.23) was significantly higher than that of the control group on the degree of willingness (M = 2.44, SD = 0.96), t (310) = 7.32, p < 0.001, Cohen’s d = 0.83. The score of the experimental group on the degree of time spent (M = 3.45, SD = 1.24) was significantly higher than that of the control group on the degree of time spent (M = 2.45, SD = 0.92), t (310) = 8.11, p < 0.001, Cohen’s d = 0.92. The score of the experimental group on IABT (M = 6.77, SD = 2.27) was significantly higher than that of the control group on IABT (M = 4.88, SD = 1.69), t (310) = 8.36, p < 0.001, Cohen’s d = 0.94. The results are shown in Figure 1. Discussion As hypothesized, the results suggested that IAB can be transmitted between strangers. That suggests that IABT, as a sort of transmission of love or caring within the Internet environment, is an example of “upstream indirect reciprocity”. The results of this study are consistent with social learning theory (Bandura, 1977), which has a certain explanatory power rewarding on the transmission effect of individual behavior. Because the impact of the form of communication stems from observational learning or experiential learning, altruistic behaviors that involve interpersonal interactions within the Internet environment are acquired, imitated, and internalized by individuals. As a result, individuals are able to transmit altruistic behaviors in the online environment, which indicates that IAB may have a positive transmission effect. Experiment 2: Internet altruistic behavior transmission have in-group favoritism Method Participants. We recruited randomly 274 students, including 80 males (29.2%) and 194 females (70.8%), aged from 17 to 24 years (M = 19.68, SD = 1.02), with an average online time of 6.88 hours. Experimental Design We adopt the between-subject design. The independent variable was the in-group/ outgroup. The dependent variable was IABT. Materials The experimental materials used to induce the receiving IAB condition were the same as those used in the pre-study. To set the in-group and out-group conditions, participants were presented with the following scenarios: Scenario setting of i n-group setting scenario . At this time, a classmate of our school sends you an email via email, which is called “help!”. The email described that he was preparing his graduation thesis. His own research scheme has been approved and recognized by his tutor. However, the current problem is that a large number of college students need to fill in his / her online questionnaire. Scenario setting of outgroup setting scenario . At this time, a student from a foreign school sends you an email via email. The email is called “help!”. The email describes that a graduate student of psychology from a foreign university is preparing his / her graduation thesis. His / her research protocol has been approved and recognized by the tutor. However, the current problem was that a large number of college students need to fill in his / her online questionnaire. Procedure Participants were randomly assigned to one of two classrooms to complete the questionnaire for their respective experimental group. The experimental situation was divided into the in-group (helping students from the same school) or the outgroup (helping academic students from different schools). Before entering the classroom, the instructors of this study required that all articles should be stored in a designated place outside the laboratory, and then enter the classroom with the participants. The instructors of this study all majoring in psychology, have received unified standardization training on the experimental process in the early stage, and do not know any participants). After being randomly assigned, a paper-based hypothetical situation questionnaire was presented to the participants. Descriptive statistics and independent t-sample test were performed on the IAB under two different conditions (outgroup control condition and in-group experimental condition). Results The results of independent sample t -test shown that the scores of the in-group on the degree of willingness (M = 3.20, SD = 1.08) are significantly higher than those of the outgroup on the degree of willingness (M = 2.75, SD = 1.11), t (272) = 3.35, p < 0.01, Cohen’s d = 0.41. The score of the in-group on the degree of time spent (M = 3.12, SD = 0.97) was significantly higher than that of the outgroup on the degree of time spent (M = 2.74, SD = 1.04), t (272) = 3.15, p < 0.01, Cohen’s d = 0.38. The score of the in-group on IABT (M = 6.32, SD = 1.72) was significantly higher than that of the outgroup on IABT (M = 5.48, SD = 1.92), t (272) = 3.81, p < 0.001, Cohen’s d = 0.46. The results are shown in Figure 2. Discussion The research results indicated that, on the measures of willingness to help, time spent helping, and overall altruism, the in-group condition showed significantly higher scores than the outgroup. In other words, there in-group favoritism was a factor in IABT between individuals, with individuals demonstrating a higher degree of IABT towards members of their in-group. This result was consistent with previous studies (Levine et al., 2005; Yu et al., 2016), and is in alignment with the wake-up cost reward model (Dovidio et al., 1991) which suggests that, compared to members of outgroups, those categorized as members of one’s in-group are imbued with increased perceived similarity, greater feelings of intimacy, a heightened sense of responsibility towards fellow members, increased willingness to help (i.e., higher wake-up), lower perceived costs of helping, and higher perceived costs of not helping (Guo et al., 2020). General Discussion The current study results support the hypothesis that IAB is transitive even between unfamiliar individuals. This illustrates that IABT can be considered a “stranger kindness transmission” within the online context. This study further demonstrated the influence of in-group favoritism in IABT. Specifically, the likelihood of IAB occurring within an in-group is higher than towards an out-group. The results of this study provide empirical evidence for IABT between college students, which can be explained by social learning theory (Bandura, 1977). The influence and results of IAB can lead to observational learning or experiential learning in that altruistic behaviors involving interpersonal interaction in online environments are learned, imitated, and then initiated by others, leading to improved individual IABT. This indicates that the IAB appears to have a positive transmission effect (Rushton, 1982). Online anonymity in particular can lower individuals’ anxiety in interactions, and virtual environments can help networked communicators overcome certain limitations allowing them to perform altruistic behaviors despite their geographical distance (Imperato et al., 2021). Furthermore, research on the transmission effect of prosocial behavior has also shown that individuals who receive help from others are then better able to consider difficulties or problems from the perspective of others (Goldman, 1989; Yu et al., 2016), and thus become more likely to choose to transmit prosocial behavior (Nowak & Sigmand, 2005). The findings of this study extended the existing research mainly based on the transmission of prosocial behavior. IAB is prosocial behavior that takes place in the online environment. In interactive interpersonal communications online, the recipient of IAB may not encounter their giver another time, however the recipient will nonetheless become the giver, transmitting their own IAB to other third-party strangers. These findings also indicate that the IAB of college students also has transitivity among groups of strangers, which is an example of upward indirect reciprocity behavior. In view of ever-increasing popularity of electronic communication, it is important to understand the characteristics of in-group favoritism applicable to the online environment. This is consistent with the self-classification theory (Tajfel et al., 1971), individuals may categorize themselves and the comparison object as belonging to a particular group. once individuals identify with a group similar to their own identity, they tend to maximize the differences between their in-group and out-group. This process facilitates the development of the in-group and helps maintain a positive self-concept (Hornsey, 2008). Furthermore, those who identify higher with an particular group are more likely to be loyal to that in-group and care more about protecting their in-groups if they feel threatened (Romano et al., 2022). Previous studies have also investigated the neurobiological mechanisms behind prosocial decision-making (Rhoads et al., 2021), finding that when one interacts with members of their own group, individuals tend to be more altruistic, conciliatory, and cooperative. This is because people identify more strongly with the members of their in-groups. As a result, they will exhibit increased prosocial connections when engaging with in-group members such as heightened cooperative behavior and interpersonal trust when engaging with in-group members (Bauer et al., 2016). Therefore, when one clearly identifies with the group they belong to, they become more likely to transmit IAB towards within their in-groups due to these common interests, evaluating their groups and fellow members in a positive fashion, and be more likely to reject members of external outgroups. Strengths and Limitations This study provides novel insights on Internet-based prosocial behavior while revealing opportunities for further research. To the best of our knowledge, this study is the first to combine IAB and indirect reciprocity to examine resulting integrated characteristics such as in-group favoritism. Furthermore, this study suggests that individuals are more motivated to demonstrate IAB towards others after recalling instances in which they themselves were aided by others. In contrast to existing studies which have focused mainly on the characteristics of givers in online contexts (Zheng et al., 2021; Zheng 2013), this study instead focused on the interpersonal interactions in the online environment, taking into account the individual characteristics of recipients and their experiences of interpersonal interactions. Finally, our findings have positive implications for fostering online community cohesion, interpersonal assistance, and cyberspace harmony during times of crisis. Despite its contributions, limitations do exist in this study. First, the setting used in this study was a laboratory environment which aimed to control external variables that could bias the results, group selection within the experiment was the only considered characteristic when measuring IABT. This narrow focus on group selection may limit the understanding of other potential factors influencing IABT outcomes. Furthermore, we did not test the mediating psychological mechanism of in-group favoritism interaction in IABT in this study. Previous studies have shown that perceived similarity and common identity may be important psychological mechanisms of in-group favoritism (Lemay & Ryan, 2021; Toprakkiran & Gordils, 2021). Future research should explore other possible psychological mechanisms, such as group recognition, which can mediate the influence of preference within a group in an IABT context. Conclusion This study utilized two experiments to determine that, in an online context, IABT does exist as a form of “kindness transmission” between strangers, and that it can be seen as an example of “upward indirect reciprocity”. Further findings confirmed the effect of in-group favoritism in IABT. This study also confirmed that individuals who receive IAB are more likely to then transmit IAB to others. Finally, the impact of in-group favoritism on IABT was examined, with results indicating, in contrast to IABT received from outgroups, the participants were more willing to receive and/or confirm to IABT received from in-group members. Declarations Conflict of interest The authors declare that they have no conflicts of interest. Ethical approval All research procedures involving human participants are in accordance with the ethical standards of the agency and / or the National Research Council, as well as the 1964 Helsinki Declaration and its subsequent amendments or similar ethical standards. Funding This research was supported by the National Natural Science Foundation of China (No. 32160200), the Hainan Provincial Natural Science Foundation of China (No. 722MS048) and the Yizhou Organization Management Research Fund. Author Contribution The authors declare that they have no conflicts of interest. Acknowledgement This research was supported by the Yizhou Organization Management Research Fund. Data Availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. References Aksoy, O. (2019). Crosscutting circles in a social dilemma: effects of social identity and inequality on cooperation. Social Science Research, 82 , 148–163. https://doi.org/10.1016/j.ssresearch.2019.04.009 Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall. Bauer, M., Blattman, C., Chytilov´ a, J., Henrich, J., Miguel, E., & Mitts, T. (2016). Can war Foster cooperation? Journal of Economic Perspectives, 30 (3), 249–274. https://doi.org/10.1257/jep.30.3.249 Desteno, D., Bartlett, M. Y., Baumann, J., Williams, L. A., & Dickens, L. (2010). Gratitude as moral sentiment: emotion-guided cooperation in economic exchange. Emotion, 10 (2), 289–293. https://doi.org/10.1037/a0017883 Dovidio, J. F., Piliavin, J. A., Gaertner, S. L., Schroeder, D. A., & Clark, R. D., III. (1991). The arousal: Cost-reward model and the process of intervention: A review of the evidence. In M. S. Clark (Ed.), Prosocial behavior (pp. 86–118). Thousand oaks, CA: Sage Publications, Inc. Essien, I., Otten, S., & Degner, J. (2020). Group evaluations as self‐group distancing: ingroup typicality moderates evaluative intergroup bias in stigmatized groups. European Journal of Social Psychology, 50 (6), 1108–1124. https://doi.org/10.1002/ejsp.2708 Goldman, A. I. (1989). Interpretation psychologized. Mind & Language, 4 (3), 161–185. https://doi.org/10.1111/j.1468-0017.1989.tb00249.x Gray, K., Ward, A. F., & Norton, M. I. (2014). Paying it forward: Generalized reciprocity and the limits of generosity. Journal of Experimental Psychology: General, 143 (1), 247–254. https://doi.org/10.1037/a0031047 Guo, R., Ding, J., & Wu, Z. (2020). How intergroup relation moderates group bias in third-party punishment. Acta Psychologica, 205, 103055. https://doi.org/10.1016/j.actpsy.2020.103055 Hornsey, M. J. (2008). Social identity theory and self-categorization theory: a historical review. Social and Personality Psychology Compass, 2 (1), 204–222. https://doi.org/10.1111/j.1751-9004.2007.00066.x Iacoviello, V., & Spears, R. (2018). “I know you expect me to favor my ingroup”: Reviving Tajfel’s original hypothesis on the generic norm explanation of ingroup favoritism. Journal of Experimental Social Psychology, 76, 88–99. https://doi.org/10.1016/j.jesp.2018.01.002 Imperato, C., Schneider, B. H., Caricati, L., Amichai-Hamburger, Y., & Mancini, T. (2021). Allport meets internet: A meta-analytical investigation of online intergroup contact and prejudice reduction. International Journal of Intercultural Relations, 81, 131–141. https://doi.org/10.1016/j.ijintrel.2021.01.006 Kawamichi, H., Sugawara, S. K., Hamano Y. H, & S, N. (2019). Prosocial behavior toward estranged persons modulates the interaction between mid-line cortical structures and the reward system. Social Neuroscience, 14 (7), 1–56. https://doi.org/10.1080/17470919.2018.1553797 Lemay, E. P. , & Ryan, J. E . (2021). Common ingroup identity, perceived similarity, and communal interracial relationships. Personality and Social Psychology Bulletin, 47 (6), 985–1003. https://doi.org/10.1177/0146167220953984 Levine, M., Prosser, A., Evans, D., & Reicher, S. (2005). Identity and emergency intervention: How social group membership and inclusiveness of group boundaries shape helping behavior. Personality and Social Psychology Bulletin, 31 (4), 443–453. https://doi.org/10.1177/0146167204271651 Melamed, D., Sweitzer, M., Simpson, B., Abernathy, J. Z., Harrell, A., & Munn, C. W. (2020). Homophily and segregation in cooperative networks. American Journal of Sociology, 125 (4), 1084–1127. https://doi.org/10.1086/708142 Mujcic, R. & Leibbrandt, A. (2017). Indirect Reciprocity and Prosocial Behaviour: Evidence from a Natural Field Experiment. The Economic Journal, 128 (611),1683–1699. https://doi.org/10.1111/ecoj.12474 Nakashima, N. A., & Flynn, F. J. (2016). Social projection in generalized exchange. Advances in Group Processes, 33 , 33–56. https://doi.org/10.1108/S0882-614520160000033002 Nowak, MA., & Sigmund, K. (2005). Evolution of indirect reciprocity. Nature, 437 (7063), 1291–1298. https://doi.org/10.1038/nature04131 Okada, I. (2020). A Review of Theoretical Studies on Indirect Reciprocity. Games, 11 (3), 1–17. https://doi.org/10.3390/g11030027 Rhoads, S. A., Cutler, J., & Marsh, A. A. (2021). A feature-based network analysis and fMRI meta-analysis reveal three distinct types of prosocial decisions. Social Cognitive and Affective Neuroscience, 16 (12), 1214–1233. https://doi.org/10.1093/scan/nsab079 Romano, A., Saral, A. S., & Wu, J. (2022). Direct and indirect reciprocity among individuals and groups. Current Opinion in Psychology, 43 , 254–259. https://doi.org/10.1016/j.copsyc.2021.08.003 Romano, A., Sutter, M., Liu, J. H., Yamagishi, T., & Balliet, D. (2021). National parochialism is ubiquitous across 42 nations around the world. Nature Communications, 12 (1), 1–8. https://doi.org/10.1038/s41467-021-24787-1 Rushton, J. P. (1982). Symposium on moral development || moral cognition, behaviorism, and social learning theory. Ethics, 92 (3), 459–467. https://doi.org/10.1086/292355 Schmid, L., Shati, P., Hilbe, C. et al. (2021). The evolution of indirect reciprocity under action and assessment generosity. Scientific Reports, 11 (1) , 1–14. https://doi.org/10.1038/s41598-021-96932-1 Skoog, E. (2020). Indirect reciprocity and trade-off paradigms in the wake of violent intergroup conflict. Evolution and Human Behavior, 42 (3), 230–238. https://doi.org/10.1016/j.evolhumbehav.2020.10.004 Stanca, L. (2009). Measuring indirect reciprocity: Whose back we scratch? Journal of Economic Psychology, 30 (2) , 190–202. https://doi.org/10.1016/j.joep.2008.07.010 Tajfel,H., Flament, C., Billig, M.G, & Bundy, R. F. (1971). Social categorization and intergroup behaviour. European Journal of Social Psychology, 1 (2), 149–177. https://doi.org/10.1002/ejsp.2420010202 Toprakkiran, S., & Gordils, J. (2021). The onset of COVID-19, common identity, and intergroup prejudice. The Journal of Social Psychology, 161 (4), 435–451. https://doi.org/10.1080/00224545.2021.1918620 Whitham, M. M. (2021). Generalized generosity: How the norm of generalized reciprocity bridges collective forms of social exchange. American Sociological Review, 86 (3), 503–531. https://doi.org/10.1177/00031224211007450 Wright, M. F., & Li, Y. (2011). The associations between young adults’ face-to-face prosocial behaviors and their online prosocial behaviors. Computers in Human Behavior, 27 (5), 1959–1962. https://doi.org/10.1016/j.chb.2011.04.019 Wu, P., Fang, J., & Liu, H. (2017). The influence of moral emotions on online helping behavior: The mediating role of moral reasoning. Acta Psychologica Sinica, 49 (12), 1559–1569. Yu, J., Zhu, L. Q., & Leslie, A. M. (2016). Children’s sharing behavior in Mini-Dictator games: The role of In-Group favoritism and theory of mind. Child Development, 87 (6), 1747–1757. https://doi.org/10.1111/cdev.12635 Zhang, H., Xu, Y., & Zhao, H. (2021). The relationship between virtuous personality and internet altruistic behavior: A moderated mediation analysis. Journal of Psychological Science, 44 (3), 619–625. Zheng, X. (2013). Theoretical and empirical research on Internet altruistic behavior. Beijing: China Social Science Press. Zheng, X., Chen, H. , Wang, Z. , Xie, F. , & Bao, Z. (2021). Links between social class and Internet altruistic behavior among undergraduates: Chain mediating role of moral identity and self-control. Current Psychology , 42, 9303–9311. https://doi.org/10.1007/s12144-021-02210-8 Additional Declarations No competing interests reported. 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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-5143264","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":359477541,"identity":"69618f5b-78f9-44c5-82a7-7974fb157381","order_by":0,"name":"Huiping Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIie3QMWsCMRTA8VceZHqaNYLc2DkguPpVEoROtTiVDA6KcjeIu9B+iI4dEw5uirre4GD3DufmptmFM6ND/kMggR+PF4BU6hkTALYxV+KI7qTMLIq8uK3HrFewsTz5Kopg2clxIA/02vtb4WPBvzY2EKbnJTGj5wx4sVbtQ4575b73pBfLTlXr3z4Iv/tpJVK8S/v/KfQSu2+19iy8TCIIMalzpOE0nHHEUa4GFAhEEVF/qPDJNhPIxkL5ih7uwreTsmmMpdGhdOeLmWW82LQTAGq9xpBUKpVK3XUDP/RNAFBQ+RAAAAAASUVORK5CYII=","orcid":"","institution":"Hainan University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Huiping","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-09-24 08:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5143264/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5143264/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68531741,"identity":"6c973788-1334-4135-a536-bc1aacd5125e","added_by":"auto","created_at":"2024-11-08 09:16:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1133297,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in degree of willingness, degree of time spent, and IABT between the experimental group and the control group\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5143264/v1/e0d58a2edeabe433afbd905f.png"},{"id":68532887,"identity":"388f4c13-63f2-469b-beb8-2f3b4437d4d0","added_by":"auto","created_at":"2024-11-08 09:24:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1000557,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in degree of willingness, degree of time spent, and IABT between in-group and outgroup\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5143264/v1/fcab2ed9d5d9a1b73a92523c.png"},{"id":87909167,"identity":"9777d40d-9941-4ed9-acaf-cd381ca06da7","added_by":"auto","created_at":"2025-07-30 09:24:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2761222,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5143264/v1/270cff19-eab8-4ea7-979d-6d64498b9517.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychological characteristics of in-group favoritism in internet altruistic behavior transmission","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAltruism is a prosocial behavior performed by a giver within appropriate situational context. It can also involve a multiple individuals over an extended timeframe, thereby forming a continuous benign social interaction (i.e., \u0026ldquo;transmission of prosocial behaviors\u0026rdquo;; Desteno et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Gray et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Stanca, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Interestingly, prosocial behavior can be transmitted interpersonally to involve cooperative behavior between strangers (Kawamichi et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Okada, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Transmitting prosocial behavior seems to operate on reciprocity (Schmid et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), of which the transmission of online prosocial behaviors remains poorly understood.\u003c/p\u003e \u003cp\u003eWith the rapid development of information technology, the Internet not only provides people with a wide range of information acquisition channels, it has also becomes an important platform for social interaction and cooperation. For instance, this digital age, Internet altruistic behavior (IAB) is becoming an everyday experience more practices and less studied. To clarify the Internet altruistic behavior transmission (IABT), we designed a preliminary experiment and two behavioral experiments to investigate the psychological characteristics of IABT based on network interpersonal interactions. Findings would provide a more comprehensive understanding Internet altruism and interpersonal relationships, and which would provide a basis for theory development and testing regarding this phenomenon in today\u0026rsquo;s active online community living.\u003c/p\u003e \u003cp\u003eInternet altruistic behavior (IAB) is a prosocial behavior that takes place in the Internet situation and does not ask for return (Zheng, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The essence IAB is consistent with that of offline or \u0026ldquo;real-life\u0026rdquo; altruistic behavior, differing only in the environments in which they occur. This distinction does imbue IAB with specific unique characteristics, however, as the virtual, timeless, and convenient natures of the online realm lend a certain complexity to IAB. IAB comprises four dimensions: online support, online guidance, online sharing, and online reminders. For instance, online support is a supportive behavior given to others on the Internet, such as showing care and encouragement towards online friends, wishing others well, and providing others with positive feedback after reading their posts. Online guidance is the act of providing others with assistance or direction on the Internet, and encompasses activities such as guiding beginners in navigating online spaces or educating them on safeguarding their privacy and personal information online. Online sharing is the act of sharing one\u0026rsquo; s own resources to others over the Internet, such as uploading and sharing study materials, or recommending useful articles to others. Finally, online reminders refer to the act of providing prompts or warnings to others on the Internet, for example to exposing illicit activities, informing fellow netizens about online scams, or reporting inappropriate online content.\u003c/p\u003e \u003cp\u003eMost of the research on IAB focuses on the psychological characteristics of the individual (Zheng et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), ignoring the interpersonal interaction situation pattern in the Internet and the experience of the individual in the Internet interaction situation. In particular, there is a lack of research on the internal psychological mechanism of IABT between the two roles (giver and recipient), that is, interpersonal interaction. This has the limitation to open with researchers having focused excessively on the individual characteristics of giver in the online environment, the significance of interpersonal dynamics within the network has been overlooked, along with the emotions and attributes of the recipient within these interpersonal interactions. Consequently, the study of the interaction between the giver and the recipient remains to be investigated. We aim to address this gap in the evidence.\u003c/p\u003e\n\u003ch3\u003eIs IAB be transmittable?\u003c/h3\u003e\n\u003cp\u003eReciprocity is the core component in prosocial behavior transmission (Whitham, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and this can be direct or indirect. Direct reciprocity is the exchange of altruistic behaviors between two individuals, which can result in mutually beneficial outcomes, while indirect reciprocity is when one provides assistance to another which, while it does not result in direct reciprocation from the recipient, it does lead to reciprocation from others further down the line (Romano et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). IAB is considered a special type of altruism (Schmid et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), in that it is enabled by the unique characteristics of the online context. The specific environment of virtual networks, with their nature of sharing, openness, and anonymity, contribute to the occurrence of IAB and help broaden the audience of potential recipients (Wright \u0026amp; Li, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This has been empirically demonstrated real-life situations via a natural experiment conducted on an online platform (Mujcic \u0026amp; Leibbrandt, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), by which individuals, upon receiving assistance from fellow drivers, were over twice as likely to exhibit similar behavior towards a third party. This observation remained consistent across various factors, including age, gender, social status, presence of onlookers, and the opportunity cost of time.\u003c/p\u003e \u003cp\u003eThe rapid growth of social media and Internet technology has dramatically increased our potential to interact extensively with strangers online. The high frequency of these online interactions may increase the likelihood of people providing feedback and assistance to one another. These studies provide substantial evidence supporting the wide dissemination of IAB, even among strangers. Therefore, based on the aforementioned empirical findings, this study proposed the first hypothesis:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 1\u003c/strong\u003e \u003cp\u003eIAB is transitive in unfamiliar groups.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe question is: Who is more likely to receive a greater amount of IAB? According to the self-classification theory (Tajfel et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1971\u003c/span\u003e), people tend to classify each other into in-group and outgroup, with a preference for in-groups and devaluation of outgroups (Hornsey, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In-group favoritism would show by preference towards those who belong to the social group (Zhang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which would also strengthen their reputation among the in-group and elevate their positive standing by sharing resources and engaging in interactions (Essien et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Iacoviello \u0026amp; Spears, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Skoog, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This effect may be from a perception of similarity (in this case, similarity in resources) heightening the favoritism which is diminished for outgroups (Nakashima \u0026amp; Flynn \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Thus, favoritism shows in prosocial behaviors towards those with whom people have a shared social identity (Aksoy \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Melamed et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Romano et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Whitham, 2018). However, people may have differing attitudes and behavioral tendencies towards in-groups versus outgroups of which the contribution to IABT is less known. The aim in the study was to investigate the phenomenon of IAB exhibits transmissibility among unfamiliar individuals and the in-group favoritism in IABT. This study proposed the following hypotheses:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 2\u003c/strong\u003e \u003cp\u003eIABT is associated with in-group favoritism more, compared the outgroup.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe present study\u003c/h2\u003e \u003cp\u003eTo further explore these hypotheses, two experiments were designed. The first experiment investigated whether an individual who received IAB was more likely to transmit IAB in a writing task. The second experiment investigated in-group favoritism among IABT by developing two self-designed scenario questionnaires.\u003c/p\u003e \u003cp\u003e\u003cem\u003eEthics compliance.\u003c/em\u003e The students participants were from the Gannan Normal University of Education Science School. This study was conducted in accordance with the principles of the Declaration of Helsinki. Participants individually consented for study. We obtained parental/giardian consent for participants under the age of 18. Participants self-reported their demographics (including gender, average daily online time, etc.). They received a pen as a reward for their participation.\u003c/p\u003e \u003cp\u003e \u003cem\u003eData analysis\u003c/em\u003e. We used SPSS (IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.) to analyze data.\u003c/p\u003e "},{"header":"Experiment 1: The occurrence of Internet altruistic behavior transmission (IABT) among strangers","content":"\u003cp\u003e\u003cstrong\u003ePre\u003c/strong\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003cstrong\u003estudy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe purpose of the\u0026nbsp;pre-study\u0026nbsp;was to explore the effectiveness of\u0026nbsp;the\u0026nbsp;text-based\u0026nbsp;materials\u0026nbsp;used to prime recipients\u0026nbsp;for receiving\u0026nbsp;IAB\u0026nbsp;by\u0026nbsp;using\u0026nbsp;a\u0026nbsp;situational recall task. Priming of IABT was done in two ways: either the participant was primed to receive IAB from another individual, or the participant was primed to carry out IAB toward another person.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;sampling.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAccording to the calculation of G*Power 3.1 software, the statistical test force is 1 \u0026minus; \u003cem\u003e\u0026beta;\u003c/em\u003e = 0.95, two-sided test ɑ = 0.05 and effect size \u003cem\u003ed\u003c/em\u003e = 0.80, conducting independent sample \u003cem\u003et\u003c/em\u003e-test results showed that the study required at least 84 participants. Thus, we recruited 84 college students\u0026nbsp;through paper questionnaires, including 55 male students (66.3%) and 29 female students (33.8%), ranging in age from 17 to 24 years old. The average online time per day\u0026nbsp;was\u0026nbsp;6.22 hours.\u0026nbsp;Participants were randomly assigned to one of two groups: accepting IAB group (\u003cem\u003en\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e=\u0026nbsp;42) and not accepting IAB group (\u003cem\u003en\u003c/em\u003e = 42).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eExperimental Design\u003c/em\u003e. \u0026nbsp; We adopted the between-subjects design. The independent variable was whether or not to accept IAB, with consists of two levels: accepting or not accepting, and the dependent variable was the degree of getting help.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Procedure\u003c/strong\u003e\u003cstrong\u003e/Instruction.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e Each group received specific instructions, as outlined below.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAccept IAB group\u003c/em\u003e: \u0026ldquo;Please recall or imagine the work or life experience in which someone committed IAB against you, that is, the experience of someone helping you on a Internet platform\u0026rdquo;. Describe your personal feelings and experiences under the above experience. Please try to exceed 200 words.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNot-accepting IAB group\u003c/em\u003e:\u0026nbsp;\u0026ldquo;Please recall or imagine your experience of communicating with netizens on an interesting topic on the Internet platform\u0026rdquo;.\u0026nbsp;All participants were required describe in detail (over 200 word).\u003c/p\u003e\n\u003cp\u003eAfter completing the above writing task, participants responded to a question on \u0026ldquo;the extent to which you have received the help of the other party and are beneficial to you\u0026rdquo; (1-7 points).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis.\u003c/em\u003e We used SPSS (IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.) to conduct an independent sample \u003cem\u003et\u003c/em\u003e-test on the degree of help obtained by the participants in the two cases of receiving and not receiving the IAB from others.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccepting IAB manipulation tests, participants who accepted IAB reported significantly higher feelings of goodwill (M\u0026nbsp;= 6.65,\u0026nbsp;SD\u0026nbsp;= 0.89) compared to those who did not accept (M\u0026nbsp;= 4.00,\u0026nbsp;SD\u0026nbsp;= 1.43),\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003et\u003c/em\u003e (82) = 9.93,\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 2.22. The results of the pre-study revealed that accepting the manipulation of IAB effectively produced the desired effect. This indicated that the selected experimental materials were appropriate. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFormal Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAs previously reported, according to the calculation of G*Power 3.1 software, the statistical test force is 1 \u0026minus; \u003cem\u003e\u0026beta;\u003c/em\u003e = 0.95, two-sided test ɑ = 0.05 and effect size \u003cem\u003ed\u003c/em\u003e = 0.80, conducting independent sample \u003cem\u003et\u003c/em\u003e-test results showed that the study required at least 84 participants. We recruited\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e312 college students (146 male and 166 female), aged from 17 to 24 years (M = 20.11, SD = 1.45), with an average online time of 6.15 hours.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Design\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe adopted the between-subjects design. The independent variable was IAB acceptance, and the dependent variable was IABT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Procedure\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eFirstly,\u0026nbsp;we used the same\u0026nbsp;self-designed acceptance scenario materials\u0026nbsp;for IAB and IABT\u0026nbsp;as the pre-study.\u0026nbsp;Participants received an email from a stranger with the subject line \u0026ldquo;Help!\u0026rdquo;. The email explained that a foreign psychology graduate student was preparing his / her graduation thesis. His / her research protocol has been approved and recognized by the tutor. However, the current problem was that he/she need search for a large number of participants to complete the relevant online questionnaires. Therefore, the email stated that the student was seeking help online to complete his/her thesis research. Participants could contribute by clicking on the link in the email and filling out the related online questionnaire.\u003c/p\u003e\n\u003cp\u003eFollowing previous research on help behavior situations online (Wu et al., 2017), participants were asked to rate two items: (1) Are you willing to help him/her? (2) How much time are you willing to spend helping? Responses to both items used a 5-point scale. The total score across these two questions served as the index for IABT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe experimental group and the control group\u003c/em\u003e. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eIndependent sample \u003cem\u003et\u003c/em\u003e-test analysis was carried out for the experimental group and the control group. The participants\u0026rsquo;\u0026nbsp;IAB in the experimental group is significantly higher than that of the control group, that is, IAB is transmitted among the unfamiliar groups of college students.\u003c/p\u003e\n\u003cp\u003eThe score of the experimental group on the degree of willingness (M = 3.35, SD = 1.23) was significantly higher than that of the control group on the degree of willingness (M = 2.44, SD = 0.96), \u003cem\u003et\u003c/em\u003e (310) = 7.32, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.83. The score of the experimental group on the degree of time spent (M = 3.45, SD = 1.24) was significantly higher than that of the control group on the degree of time spent (M = 2.45, SD = 0.92), \u003cem\u003et\u003c/em\u003e (310) = 8.11, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.92. The score of the experimental group on IABT (M = 6.77, SD = 2.27) was significantly higher than that of the control group on IABT (M = 4.88, SD = 1.69), \u003cem\u003et\u003c/em\u003e (310) = 8.36, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.94. The results are shown in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs hypothesized, the results suggested that IAB can be transmitted between strangers. That suggests that IABT, as a sort of transmission of love or caring within the Internet environment, is an example of \u0026ldquo;upstream indirect reciprocity\u0026rdquo;. The results of this study are consistent with social learning theory (Bandura, 1977), which has a certain explanatory power rewarding on the transmission effect of individual behavior. Because the impact of the form of communication stems from observational learning or experiential learning, altruistic behaviors that involve interpersonal interactions within the Internet environment are acquired, imitated, and internalized by individuals. As a result, individuals are able to transmit altruistic behaviors in the online environment, which indicates that IAB may have a positive transmission effect.\u003c/p\u003e"},{"header":"Experiment 2: Internet altruistic behavior transmission have in-group favoritism","content":"\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants. \u0026nbsp;\u003c/strong\u003eWe recruited\u0026nbsp;randomly 274\u0026nbsp;students, including 80 males (29.2%) and 194 females (70.8%), aged from 17 to 24 years (M\u0026nbsp;=\u0026nbsp;19.68,\u0026nbsp;SD\u0026nbsp;= 1.02),\u0026nbsp;with an average online time of 6.88 hours.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Design\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe\u0026nbsp;adopt\u0026nbsp;the\u0026nbsp;between-subject design. The independent variable\u0026nbsp;was\u0026nbsp;the in-group/ outgroup. The dependent variable\u0026nbsp;was\u0026nbsp;IABT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003eThe experimental materials used to induce the receiving IAB condition were the same as those used in the pre-study. To set the in-group and out-group conditions, participants were presented with the following scenarios:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScenario setting of\u0026nbsp;\u003c/em\u003e\u003cem\u003ei\u003c/em\u003e\u003cem\u003en-group setting scenario\u003c/em\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAt this time, a classmate of our school sends you an email via email, which is called \u0026ldquo;help!\u0026rdquo;. The email described that he was preparing his graduation thesis. His own research scheme has been approved and recognized by his tutor. However, the current problem is that a large number of college students need to fill in his / her online questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScenario setting of outgroup setting scenario\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAt this time, a student from a foreign school sends you an email via email. The email is called \u0026ldquo;help!\u0026rdquo;. The email describes that a graduate student of psychology from a foreign university is preparing his / her graduation thesis. His / her research protocol has been approved and recognized by the tutor. However, the current problem was that a large number of college students need to fill in his / her online questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Participants were randomly assigned to one of two classrooms to complete the questionnaire for their respective experimental group. The experimental situation was divided into the in-group (helping students from the same school) or the outgroup (helping academic students from different schools). Before entering the classroom, the instructors of this study required that all articles should be stored in a designated place outside the laboratory, and then enter the classroom with the participants. The instructors of this study all majoring in psychology, have received unified standardization training on the experimental process in the early stage, and do not know any participants). After being randomly assigned, a\u0026nbsp;paper-based hypothetical situation questionnaire was presented to the participants. Descriptive statistics and independent t-sample test were performed on the IAB under two different conditions (outgroup control condition and in-group experimental condition).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of independent sample \u003cem\u003et\u003c/em\u003e-test shown that the scores of the in-group on the degree of willingness (M\u0026nbsp;= 3.20,\u0026nbsp;SD\u0026nbsp;= 1.08) are significantly higher than those of the outgroup on the degree of willingness (M\u0026nbsp;= 2.75,\u0026nbsp;SD\u0026nbsp;= 1.11),\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003et\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e(272) = 3.35, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.41. The score of the in-group on the degree of time spent (M = 3.12, SD = 0.97) was significantly higher than that of the outgroup on the degree of time spent (M = 2.74, SD = 1.04), \u003cem\u003et\u003c/em\u003e (272) = 3.15, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.38. The score of the in-group on IABT (M = 6.32, SD = 1.72) was significantly higher than that of the outgroup on IABT (M = 5.48, SD = 1.92), \u003cem\u003et\u003c/em\u003e (272) = 3.81, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.46. The results are shown in Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research results indicated that, on the measures of willingness to help, time spent helping, and overall altruism, the in-group condition showed significantly higher scores than the outgroup. In other words, there in-group favoritism was a factor in IABT between individuals, with individuals demonstrating a higher degree of IABT towards members of their in-group. This result was consistent with previous studies (Levine et al., 2005; Yu et al., 2016), and is in alignment with the wake-up cost reward model (Dovidio et al., 1991) which suggests that, compared to members of outgroups, those categorized as members of one\u0026rsquo;s in-group are imbued with increased perceived similarity, greater feelings of intimacy, a heightened sense of responsibility towards fellow members, increased willingness to help (i.e., higher wake-up), lower perceived costs of helping, and higher perceived costs of not helping (Guo et al., 2020).\u0026nbsp;\u003c/p\u003e"},{"header":"General Discussion","content":"\u003cp\u003eThe current\u0026nbsp;study results\u0026nbsp;support the hypothesis that IAB is transitive\u0026nbsp;even between\u0026nbsp;unfamiliar individuals. This illustrates that IABT can be considered a\u0026nbsp;\u0026ldquo;stranger kindness transmission\u0026rdquo;\u0026nbsp;within\u0026nbsp;the\u0026nbsp;online context. This study further demonstrated the influence of in-group favoritism in IABT. Specifically, the likelihood of IAB occurring within an in-group is higher than towards an out-group.\u003c/p\u003e\n\u003cp\u003eThe results of this study provide empirical evidence for IABT\u0026nbsp;between\u0026nbsp;college students, which can be explained by social learning theory\u0026nbsp;(Bandura, 1977).\u0026nbsp;The influence and results of IAB can lead to observational learning or experiential learning in that altruistic behaviors involving interpersonal interaction in\u0026nbsp;online\u0026nbsp;environments\u0026nbsp;are learned, imitated,\u0026nbsp;and\u0026nbsp;then\u0026nbsp;initiated by others, leading to improved individual\u0026nbsp;IABT. This indicates that the IAB appears to have a positive transmission effect (Rushton, 1982).\u0026nbsp;Online anonymity\u0026nbsp;in particular\u0026nbsp;can\u0026nbsp;lower individuals\u0026rsquo;\u0026nbsp;anxiety in interactions, and virtual environments can help networked\u0026nbsp;communicators overcome\u0026nbsp;certain\u0026nbsp;limitations allowing them to perform altruistic behaviors despite their geographical distance\u0026nbsp;(Imperato et al., 2021).\u0026nbsp;Furthermore,\u0026nbsp;research on the transmission effect of prosocial behavior\u0026nbsp;has\u0026nbsp;also\u0026nbsp;shown\u0026nbsp;that individuals who receive help from others are\u0026nbsp;then\u0026nbsp;better able to consider\u0026nbsp;difficulties or problems\u0026nbsp;from the perspective of others (Goldman, 1989; Yu et al., 2016), and thus\u0026nbsp;become more likely to\u0026nbsp;choose to transmit prosocial behavior (Nowak \u0026amp; Sigmand, 2005).\u0026nbsp;The findings of this study\u0026nbsp;extended the existing\u0026nbsp;research mainly based on the transmission of prosocial behavior. IAB\u0026nbsp;is\u0026nbsp;prosocial behavior that takes place\u0026nbsp;in the online environment. In interactive interpersonal communications\u0026nbsp;online, the recipient of IAB may not encounter their giver another time, however the recipient will nonetheless become the giver, transmitting their own IAB to\u0026nbsp;other\u0026nbsp;third-party strangers.\u0026nbsp;These findings also\u0026nbsp;indicate\u0026nbsp;that the IAB of college students also has transitivity\u0026nbsp;among groups of\u0026nbsp;strangers, which is an example of\u0026nbsp;upward indirect reciprocity behavior.\u003c/p\u003e\n\u003cp\u003eIn\u0026nbsp;view of\u0026nbsp;ever-increasing popularity of electronic communication, it is important to understand\u0026nbsp;the characteristics\u0026nbsp;of in-group favoritism applicable\u0026nbsp;to the online environment.\u0026nbsp;This is consistent with\u0026nbsp;the\u0026nbsp;self-classification theory\u0026nbsp;(Tajfel et al., 1971), individuals may categorize themselves and the comparison object as belonging to a particular group.\u0026nbsp;once individuals identify with a group similar to their own identity, they tend to maximize the differences between their in-group and out-group. This process facilitates the development of the in-group and helps maintain a positive self-concept (Hornsey, 2008).\u0026nbsp;Furthermore, those who identify\u0026nbsp;higher\u0026nbsp;with an particular\u0026nbsp;group are more likely to be loyal to\u0026nbsp;that in-group and care\u0026nbsp;more\u0026nbsp;about protecting their\u0026nbsp;in-groups\u0026nbsp;if\u0026nbsp;they\u0026nbsp;feel\u0026nbsp;threatened (Romano et al., 2022). Previous studies\u0026nbsp;have also investigated the neurobiological mechanisms behind prosocial decision-making\u0026nbsp;(Rhoads et al., 2021), finding that when one\u0026nbsp;interacts\u0026nbsp;with members of their own\u0026nbsp;group, individuals tend to be more altruistic, conciliatory,\u0026nbsp;and cooperative. This is because people identify more strongly with\u0026nbsp;the\u0026nbsp;members of their in-groups. As a result, they\u0026nbsp;will\u0026nbsp;exhibit increased prosocial connections when engaging with in-group members\u0026nbsp;such as heightened cooperative behavior and interpersonal trust\u0026nbsp;when engaging with in-group members\u0026nbsp;(Bauer et al., 2016). Therefore, when\u0026nbsp;one\u0026nbsp;clearly identifies\u0026nbsp;with the group they belong to, they\u0026nbsp;become\u0026nbsp;more likely to transmit IAB\u0026nbsp;towards\u0026nbsp;within their\u0026nbsp;in-groups due to\u0026nbsp;these\u0026nbsp;common interests, evaluating their groups and\u0026nbsp;fellow\u0026nbsp;members in a positive\u0026nbsp;fashion, and\u0026nbsp;be\u0026nbsp;more likely to reject members of external\u0026nbsp;outgroups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eand Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;provides\u0026nbsp;novel insights on\u0026nbsp;Internet-based\u0026nbsp;prosocial behavior\u0026nbsp;while revealing opportunities for further research.\u0026nbsp;To the best of our knowledge,\u0026nbsp;this study is the first to\u0026nbsp;combine\u0026nbsp;IAB\u0026nbsp;and indirect reciprocity\u0026nbsp;to\u0026nbsp;examine\u0026nbsp;resulting\u0026nbsp;integrated characteristics\u0026nbsp;such as in-group favoritism. Furthermore, this\u0026nbsp;study suggests that individuals are more\u0026nbsp;motivated to demonstrate IAB towards\u0026nbsp;others\u0026nbsp;after recalling instances\u0026nbsp;in which\u0026nbsp;they themselves were aided by others. In contrast to existing studies which have focused\u0026nbsp;mainly\u0026nbsp;on the characteristics of givers in online contexts\u0026nbsp;(Zheng et al., 2021; Zheng 2013), this study instead\u0026nbsp;focused on\u0026nbsp;the interpersonal interactions in the online environment, taking into account the individual characteristics of recipients and their experiences\u0026nbsp;of\u0026nbsp;interpersonal interactions.\u0026nbsp;Finally,\u0026nbsp;our findings\u0026nbsp;have\u0026nbsp;positive implications for fostering online community cohesion, interpersonal assistance, and cyberspace harmony during times of crisis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite its contributions, limitations do exist in this study. First, the setting used in this study was a laboratory environment which aimed to control external variables that could bias the results, group selection within the experiment was the only considered characteristic when measuring IABT. This narrow focus on group selection may limit the understanding of other potential factors influencing IABT outcomes. Furthermore, we did not test the mediating psychological mechanism of in-group favoritism interaction in IABT in this study. Previous studies have shown that perceived similarity and common identity may be important psychological mechanisms of in-group favoritism (Lemay \u0026amp; Ryan, 2021; Toprakkiran \u0026amp; Gordils, 2021). Future research should explore other possible psychological mechanisms, such as group recognition, which can mediate the influence of preference within a group in an IABT context.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study utilized two experiments to determine that, in an online context, IABT does exist as a form of \u0026ldquo;kindness transmission\u0026rdquo; between strangers, and that it can be seen as an example of \u0026ldquo;upward indirect reciprocity\u0026rdquo;. Further findings confirmed the effect of in-group favoritism in IABT. This study also confirmed that individuals who receive IAB are more likely to then transmit IAB to others. Finally, the impact of in-group favoritism on IABT was examined, with results indicating, in contrast to IABT received from outgroups, the participants were more willing to receive and/or confirm to IABT received from in-group members.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003e All research procedures involving human participants are in accordance with the ethical standards of the agency and / or the National Research Council, as well as the 1964 Helsinki Declaration and its subsequent amendments or similar ethical standards.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was supported by the National Natural Science Foundation of China (No. 32160200), the Hainan Provincial Natural Science Foundation of China (No. 722MS048) and the Yizhou Organization Management Research Fund.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis research was supported by the Yizhou Organization Management Research Fund.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAksoy, O. (2019). Crosscutting circles in a social dilemma: effects of social identity and inequality on cooperation. \u003cem\u003eSocial Science Research, 82\u003c/em\u003e, 148\u0026ndash;163. https://doi.org/10.1016/j.ssresearch.2019.04.009\u003c/li\u003e\n\u003cli\u003eBandura, A. (1977). \u003cem\u003eSocial Learning Theory. \u003c/em\u003eEnglewood Cliffs, NJ: Prentice Hall.\u003c/li\u003e\n\u003cli\u003eBauer, M., Blattman, C., Chytilov\u0026acute; a, J., Henrich, J., Miguel, E., \u0026amp; Mitts, T. (2016). Can war Foster cooperation? \u003cem\u003eJournal of Economic Perspectives, 30\u003c/em\u003e(3), 249\u0026ndash;274. https://doi.org/10.1257/jep.30.3.249\u003c/li\u003e\n\u003cli\u003eDesteno, D., Bartlett, M. Y., Baumann, J., Williams, L. A., \u0026amp; Dickens, L. (2010). Gratitude as moral sentiment: emotion-guided cooperation in economic exchange. \u003cem\u003eEmotion, 10\u003c/em\u003e(2), 289\u0026ndash;293. https://doi.org/10.1037/a0017883\u003c/li\u003e\n\u003cli\u003eDovidio, J. F., Piliavin, J. A., Gaertner, S. L., Schroeder, D. A., \u0026amp; Clark, R. D., III. (1991). The arousal: Cost-reward model and the process of intervention: A review of the evidence. In M. S. Clark (Ed.), \u003cem\u003eProsocial behavior\u003c/em\u003e (pp. 86\u0026ndash;118). Thousand oaks, CA: Sage Publications, Inc.\u003c/li\u003e\n\u003cli\u003eEssien, I., Otten, S., \u0026amp; Degner, J. (2020). Group evaluations as self‐group distancing: ingroup typicality moderates evaluative intergroup bias in stigmatized groups. \u003cem\u003eEuropean Journal of Social Psychology, 50\u003c/em\u003e(6), 1108\u0026ndash;1124. https://doi.org/10.1002/ejsp.2708\u003c/li\u003e\n\u003cli\u003eGoldman, A. I. (1989). Interpretation psychologized. \u003cem\u003eMind \u0026amp; Language, 4\u003c/em\u003e(3), 161\u0026ndash;185. https://doi.org/10.1111/j.1468-0017.1989.tb00249.x\u003c/li\u003e\n\u003cli\u003eGray, K., Ward, A. F., \u0026amp; Norton, M. I. (2014). Paying it forward: Generalized reciprocity and the limits of generosity. \u003cem\u003eJournal of Experimental Psychology: General, 143\u003c/em\u003e(1), 247\u0026ndash;254. https://doi.org/10.1037/a0031047\u003c/li\u003e\n\u003cli\u003eGuo, R., Ding, J., \u0026amp; Wu, Z. (2020). How intergroup relation moderates group bias in third-party punishment.\u003cem\u003e Acta Psychologica, 205, \u003c/em\u003e103055. https://doi.org/10.1016/j.actpsy.2020.103055\u003c/li\u003e\n\u003cli\u003eHornsey, M. J. (2008). Social identity theory and self-categorization theory: a historical review. \u003cem\u003eSocial and Personality Psychology Compass, 2\u003c/em\u003e(1), 204\u0026ndash;222. https://doi.org/10.1111/j.1751-9004.2007.00066.x\u003c/li\u003e\n\u003cli\u003eIacoviello, V., \u0026amp; Spears, R. (2018). \u0026ldquo;I know you expect me to favor my ingroup\u0026rdquo;: Reviving Tajfel\u0026rsquo;s original hypothesis on the generic norm explanation of ingroup favoritism. \u003cem\u003eJournal of Experimental Social Psychology, 76,\u003c/em\u003e 88\u0026ndash;99. https://doi.org/10.1016/j.jesp.2018.01.002\u003c/li\u003e\n\u003cli\u003eImperato, C., Schneider, B. H., Caricati, L., Amichai-Hamburger, Y., \u0026amp; Mancini, T. (2021). Allport meets internet: A meta-analytical investigation of online intergroup contact and prejudice reduction. \u003cem\u003eInternational Journal of Intercultural Relations, 81,\u003c/em\u003e 131\u0026ndash;141. https://doi.org/10.1016/j.ijintrel.2021.01.006\u003c/li\u003e\n\u003cli\u003eKawamichi, H., Sugawara, S. K., Hamano Y. H, \u0026amp; S, N. (2019). Prosocial behavior toward estranged persons modulates the interaction between mid-line cortical structures and the reward system. \u003cem\u003eSocial Neuroscience, 14\u003c/em\u003e(7), 1\u0026ndash;56. https://doi.org/10.1080/17470919.2018.1553797\u003c/li\u003e\n\u003cli\u003eLemay, E. P. , \u0026amp; Ryan, J. E . (2021). Common ingroup identity, perceived similarity, and communal interracial relationships. \u003cem\u003ePersonality and Social Psychology Bulletin, 47\u003c/em\u003e(6), 985\u0026ndash;1003. https://doi.org/10.1177/0146167220953984\u003c/li\u003e\n\u003cli\u003eLevine, M., Prosser, A., Evans, D., \u0026amp; Reicher, S. (2005). Identity and emergency intervention: How social group membership and inclusiveness of group boundaries shape helping behavior. \u003cem\u003ePersonality and Social Psychology Bulletin, 31\u003c/em\u003e(4), 443\u0026ndash;453. https://doi.org/10.1177/0146167204271651\u003c/li\u003e\n\u003cli\u003eMelamed, D., Sweitzer, M., Simpson, B., Abernathy, J. Z., Harrell, A., \u0026amp; Munn, C. W. (2020). Homophily and segregation in cooperative networks.\u003cem\u003e American Journal of Sociology, 125\u003c/em\u003e(4), 1084\u0026ndash;1127. https://doi.org/10.1086/708142\u003c/li\u003e\n\u003cli\u003eMujcic, R. \u0026amp; Leibbrandt, A. (2017). Indirect Reciprocity and Prosocial Behaviour: Evidence from a Natural Field Experiment. \u003cem\u003eThe Economic Journal, 128\u003c/em\u003e(611),1683\u0026ndash;1699. https://doi.org/10.1111/ecoj.12474\u003c/li\u003e\n\u003cli\u003eNakashima, N. A., \u0026amp; Flynn, F. J. (2016). Social projection in generalized exchange. \u003cem\u003eAdvances in Group Processes, 33\u003c/em\u003e, 33\u0026ndash;56. https://doi.org/10.1108/S0882-614520160000033002\u003c/li\u003e\n\u003cli\u003eNowak, MA., \u0026amp; Sigmund, K. (2005). Evolution of indirect reciprocity. \u003cem\u003eNature, 437\u003c/em\u003e(7063), 1291\u0026ndash;1298. https://doi.org/10.1038/nature04131\u003c/li\u003e\n\u003cli\u003eOkada, I. (2020). A Review of Theoretical Studies on Indirect Reciprocity. \u003cem\u003eGames, 11\u003c/em\u003e(3), 1\u0026ndash;17. https://doi.org/10.3390/g11030027\u003c/li\u003e\n\u003cli\u003eRhoads, S. A., Cutler, J., \u0026amp; Marsh, A. A. (2021). A feature-based network analysis and fMRI meta-analysis reveal three distinct types of prosocial decisions. \u003cem\u003eSocial \u003c/em\u003e\u003cem\u003eCognitive and Affective Neuroscience, 16\u003c/em\u003e(12), 1214\u0026ndash;1233. https://doi.org/10.1093/scan/nsab079\u003c/li\u003e\n\u003cli\u003eRomano, A., Saral, A. S., \u0026amp; Wu, J. (2022). Direct and indirect reciprocity among individuals and groups. \u003cem\u003eCurrent Opinion in Psychology, 43\u003c/em\u003e, 254\u0026ndash;259. https://doi.org/10.1016/j.copsyc.2021.08.003\u003c/li\u003e\n\u003cli\u003eRomano, A., Sutter, M., Liu, J. H., Yamagishi, T., \u0026amp; Balliet, D. (2021). National parochialism is ubiquitous across 42 nations around the world. \u003cem\u003eNature Communications, 12\u003c/em\u003e(1), 1\u0026ndash;8. https://doi.org/10.1038/s41467-021-24787-1\u003c/li\u003e\n\u003cli\u003eRushton, J. P. (1982). Symposium on moral development || moral cognition, behaviorism, and social learning theory. \u003cem\u003eEthics, 92\u003c/em\u003e(3), 459\u0026ndash;467. https://doi.org/10.1086/292355\u003c/li\u003e\n\u003cli\u003eSchmid, L., Shati, P., Hilbe, C. et al. (2021). The evolution of indirect reciprocity under action and assessment generosity. \u003cem\u003eScientific Reports, 11\u003c/em\u003e(1)\u003cem\u003e,\u003c/em\u003e 1\u0026ndash;14. https://doi.org/10.1038/s41598-021-96932-1\u003c/li\u003e\n\u003cli\u003eSkoog, E. (2020). Indirect reciprocity and trade-off paradigms in the wake of violent intergroup conflict. \u003cem\u003eEvolution and Human Behavior, 42\u003c/em\u003e(3), 230\u0026ndash;238. https://doi.org/10.1016/j.evolhumbehav.2020.10.004\u003c/li\u003e\n\u003cli\u003eStanca, L. (2009). Measuring indirect reciprocity: Whose back we scratch? \u003cem\u003eJournal of Economic Psychology, 30\u003c/em\u003e(2)\u003cem\u003e, \u003c/em\u003e190\u0026ndash;202. https://doi.org/10.1016/j.joep.2008.07.010\u003c/li\u003e\n\u003cli\u003eTajfel,H., Flament, C., Billig, M.G, \u0026amp; Bundy, R. F. (1971). Social categorization and intergroup behaviour. \u003cem\u003eEuropean Journal of Social Psychology, 1\u003c/em\u003e(2), 149\u0026ndash;177. https://doi.org/10.1002/ejsp.2420010202\u003c/li\u003e\n\u003cli\u003eToprakkiran, S., \u0026amp; Gordils, J. (2021). The onset of COVID-19, common identity, and intergroup prejudice. \u003cem\u003eThe Journal of Social Psychology, 161\u003c/em\u003e(4), 435\u0026ndash;451. https://doi.org/10.1080/00224545.2021.1918620\u003c/li\u003e\n\u003cli\u003eWhitham, M. M. (2021). Generalized generosity: How the norm of generalized reciprocity bridges collective forms of social exchange. \u003cem\u003eAmerican Sociological Review, 86\u003c/em\u003e(3), 503\u0026ndash;531. https://doi.org/10.1177/00031224211007450\u003c/li\u003e\n\u003cli\u003eWright, M. F., \u0026amp; Li, Y. (2011). The associations between young adults\u0026rsquo; face-to-face prosocial behaviors and their online prosocial behaviors. \u003cem\u003eComputers in Human Behavior, 27\u003c/em\u003e(5), 1959\u0026ndash;1962. https://doi.org/10.1016/j.chb.2011.04.019\u003c/li\u003e\n\u003cli\u003eWu, P., Fang, J., \u0026amp; Liu, H. (2017). The influence of moral emotions on online helping behavior: The mediating role of moral reasoning. \u003cem\u003eActa Psychologica Sinica, 49\u003c/em\u003e(12), 1559\u0026ndash;1569.\u003c/li\u003e\n\u003cli\u003eYu, J., Zhu, L. Q., \u0026amp; Leslie, A. M. (2016). Children\u0026rsquo;s sharing behavior in Mini-Dictator games: The role of In-Group favoritism and theory of mind. \u003cem\u003eChild Development, 87\u003c/em\u003e(6), 1747\u0026ndash;1757. https://doi.org/10.1111/cdev.12635\u003c/li\u003e\n\u003cli\u003eZhang, H., Xu, Y., \u0026amp; Zhao, H. (2021). The relationship between virtuous personality and internet altruistic behavior: A moderated mediation analysis. \u003cem\u003eJournal of Psychological Science, 44\u003c/em\u003e(3), 619\u0026ndash;625.\u003c/li\u003e\n\u003cli\u003eZheng, X. (2013). \u003cem\u003eTheoretical and empirical research on Internet altruistic behavior. \u003c/em\u003eBeijing: China Social Science Press. \u003c/li\u003e\n\u003cli\u003eZheng, X., Chen, H. , Wang, Z. , Xie, F. , \u0026amp; Bao, Z. (2021). Links between social class and Internet altruistic behavior among undergraduates: Chain mediating role of moral identity and self-control. \u003cem\u003eCurrent Psychology\u003c/em\u003e, \u003cem\u003e42,\u003c/em\u003e 9303\u0026ndash;9311. https://doi.org/10.1007/s12144-021-02210-8\u003c/li\u003e\n\u003c/ol\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":"internet altruistic behavior, internet altruistic behavior transmission, in-group favoritism, indirect reciprocity","lastPublishedDoi":"10.21203/rs.3.rs-5143264/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5143264/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u0026ldquo;Pay-it-forward reciprocity\u0026rdquo; refers to the phenomenon of altruistic behavior being transmitted between strangers when one stranger shows goodwill toward a third party. This study implemented two experiments to explore the characteristics of Internet altruistic behavior transmission (IABT). Experiment 1 (participants: n\u0026thinsp;=\u0026thinsp;312, college students, mean age\u0026thinsp;=\u0026thinsp;20.11 years, SD\u0026thinsp;=\u0026thinsp;1.45) used a specifically-designed situational questionnaire and situational recall tasks to examine whether Internet altruistic behavior (IAB) can be transmitted between strangers. Results showed that the level of IAB in the experimental group was higher compared to that of participants who did not experience IAB from strangers. That is, individuals who received online help from others tended to then help other strangers later on. Experiment 2 (participants: n\u0026thinsp;=\u0026thinsp;274, college students, mean age\u0026thinsp;=\u0026thinsp;19.68 years, SD\u0026thinsp;=\u0026thinsp;1.02) investigated whether an in-group favoritism effect was present in IABT, and revealed that individuals showed a greater degree of IABT toward in-groups than to outgroups. These findings are consistent with the self-classification theory, which says that individuals categorize themselves into different groups based on similarities and differences with others, and are inclined to adopt behaviors that align with the identity of the categorized group, this implies that individuals are more likely to transmit IAB to their in-group.\u003c/p\u003e","manuscriptTitle":"Psychological characteristics of in-group favoritism in internet altruistic behavior transmission","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-08 09:16:54","doi":"10.21203/rs.3.rs-5143264/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":"078cf2ab-0fb1-4824-9cfe-89239699069a","owner":[],"postedDate":"November 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-30T09:24:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-08 09:16:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5143264","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5143264","identity":"rs-5143264","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}