题名

邊緣人的力量:以代理人基模型檢視謠言傳播

并列篇名

The Power of Marginality: Agent-Based Modeling for Rumor Spreading

DOI

10.29843/JCCIS.202307_(45).0004

作者

王昱凱(Yu-Kai Wang);陶振超(Chen-Chao Tao )

关键词

代理人基模型 ; 迴聲室 ; 結構洞 ; 意見領袖 ; 複雜系統 ; 邊緣人 ; 謠言 ; Agent-based Modeling ; Complex Systems ; Echo Chamber ; Opinion Leaders ; Marginality ; Rumor ; Structural Hole

期刊名称

資訊社會研究

卷期/出版年月

45期(2023 / 07 / 01)

页次

91 - 141

内容语文

繁體中文;英文

中文摘要

社交媒體中謠言經常來自追隨者數量不高的帳號,但傳播效果卻能比由意見領袖散播的真實訊息更為優秀。此一違反直覺的現象反映出謠言傳播的複雜性,我們將其稱為邊緣人的力量。本研究以代理人基模型(Agent-base modeling)來分析邊緣人與意見領袖傳播謠言的效果差異。結果顯示,儘管意見領袖的總影響人數較多,但卻存在明顯的上限。而邊緣人能通過較少的連結數影響更多的使用者,且此一特徵會隨著時間緩慢成長,顯示出較穩定的影響動態。其次,相較於邊緣人,意見領袖散布的謠言會加速群體意見的分裂速度,增加網絡中的迴聲室數量;這些結果暗示了我們不應過份高估意見領袖傳播訊息的能力,同時應當重視社交媒體任何造謠的使用者;從方法面而論,本研究引入了複雜系統的概念與研究方法,提供未來從事謠言傳播研究的相關建議。

英文摘要

Social media rumors often originate from accounts with a low number of followers, yet these rumors can surpass the spread of genuine information disseminated by opinion leaders. This counterintuitive phenomenon is indicative of the complexity of rumor propagation, which we refer to as the power of marginality. In this study, an agent-based modeling approach was employed to examine the disparity in the impact of rumor propagation between marginality and opinion leaders. The findings reveal that while the overall influence of opinion leaders is substantial, it has a discernible upper limit. Marginality, on the other hand, can exert greater influence on a larger number of users with fewer connections, and this attribute grows gradually over time, illustrating a more stable influence dynamic. Additionally, the dissemination of rumors by opinion leaders accelerates the fragmentation of group opinions and increases the number of echo chambers within the network compared to marginality. These results underscore the need to avoid overestimating the capacity of opinion leaders to disseminate information and to pay attention to any social media users engaging in rumormongering. Methodologically, this study employs research techniques that can analyze complex systems and provide recommendations for future research on rumor propagation.

主题分类 基礎與應用科學 > 資訊科學
社會科學 > 社會學
社會科學 > 傳播學
参考文献
  1. An, J.,Quercia, D.,Cha, M.,Gummadi, K.,Crowcroft, J.(2014).Sharing political news: the balancing act of intimacy and socialization in selective exposure.EPJ Data Science,3(1),1-21.
  2. Axelrod, R.(1997).The dissemination of culture.Journal of Conflict Resolution,41(2),203-226.
  3. Badham, J.,Kee, F.,Hunter, R. F.(2018).Simulating network intervention strategies: Implications for adoption of behaviour.Network Science,6(2),265-280.
  4. Badham, J.,Kee, F.,Hunter, R. F.(2021).Network structure influence on simulated network interventions for behaviour change.Social Networks,64,55-62.
  5. Bail, C. A.,Argyle, L. P.,Brown, T. W.,Bumpus, J. P.,Chen, H.,Hunzaker, M. B. F.,Lee, J.,Mann, M.,Merhout, F.,Volfovsky, A.(2018).Exposure to opposing views on social media can increase political polarization.Proceedings of the National Academy of Sciences,115(37),9216-9221.
  6. Bakshy, E.,Rosenn, I.,Marlow, C.,Adamic, L.(2012).The role of social networks in information diffusion.WWW’12 - Proceedings of the 21st Annual Conference on World Wide Web
  7. Barabasi, A. L.,Albert, R.(1999).Emergence of scaling in random networks.Science,286(5439),509-512.
  8. Bergström, A.,Jervelycke Belfrage, M.(2018).News in social media: Incidental consumption and the role of opinion leaders.Digital journalism,6(5),583-598.
  9. Bessi, A.,Ferrara, E.(2016).Social bots distort the 2016 U.S. Presidential election online discussion.First Monday,21
  10. Bessi, A.,Petroni, F.,Vicario, M. D.,Zollo, F.,Anagnostopoulos, A.,Scala, A.,Caldarelli, G.,Quattrociocchi, W.(2016).Homophily and polarization in the age of misinformation.The European Physical Journal Special Topics,225(10),2047-2059.
  11. Bonabeau, E.(2002).Agent-based modeling: methods and techniques for simulating human systems.Proceedings of the National Academy of Sciences,99(suppl_3),7280-7287.
  12. Boxell, L.,Gentzkow, M.,Shapiro, J. M.(2017).Greater internet use is not associated with faster growth in political polarization among US demographic groups.Proceedings of the National Academy of Sciences,114(40),10612-10617.
  13. Bright, J.,Marchal, N.,Ganesh, B.,Rudinac, S.(2022).How do individuals in a radical echo chamber react to opposing views? Evidence from a Content Analysis of Stormfront.Human Communication Research,48(1),116-145.
  14. Brown, J. J.,Reingen, P. H.(1987).Social ties and word-of-mouth referral behavior.Journal of Consumer Research,14,350-362.
  15. Burt, R. S.(2004).Structural holes and good ideas.American Journal of Sociology,110(2),349-399.
  16. Burt, R. S.(1992).Structural Holes: The Social Structure of Competition.Harvard University Press.
  17. Burt, R. S.(1999).The social capital of opinion leaders.The Annals of The American Academy of Political and Social Science,566,37-54.
  18. Centola, D.(2010).The spread of behavior in an online social network experiment.Science,329(5996),1194-1197.
  19. Centola, D.,Gonzalez-Avella, J. C.,Eguiluz, V. M.,San Miguel, M.(2007).Homophily, cultural drift and the co-evolution of cultural groups.Journal of Conflict Resolution,51(6),905-929.
  20. Centola, D.,Macy, M.(2007).Complex contagions and the weakness of long ties.American Journal of Sociology,113(3),702-734.
  21. Cepic, D.,Tonkovic, Z.(2020).How social ties transcend class boundaries? Network variability as tool for exploring occupational homophily.Social Networks,62,33-42.
  22. Champely, S.(2016). pwr: Basic Functions for Power Analysis. In http://CRAN.R-project.org/package=pwr
  23. Choi, S.(2015).The two-step flow of communication in Twitter-based public forums.Social Science Computer Review,33(6),696-711.
  24. Cinelli, M.,De Francisci Morales, G.,Galeazzi, A.,Quattrociocchi, W.,Starnini, M.(2021).The echo chamber effect on social media.Proceedings of the National Academy of Sciences,118(9),e2023301118.
  25. Cohen, J.(1992).A power primer.Psychological Bulletin,112(1),155-159.
  26. Coulter, R. A.,Feick, L. F.,Price, L. L.(2002).Changing faces: cosmetics opinion leadership among women in the new Hungary.European Journal of Marketing,36(11/12),1287-1308.
  27. Crutchfield, J. P.(1994).The calculi of emergence: computation, dynamics and induction.Physica D-Nonlinear Phenomena,75(1-3),11-54.
  28. Del Vicario, M.,Bessi, A.,Zollo, F.,Petroni, F.,Scala, A.,Caldarelli, G.,Stanley, H. E.,Quattrociocchi, W.(2016).The spreading of misinformation online.Proceedings of the National Academy of Sciences,113(3),554-559.
  29. Diaz-Martin, A. M.,Schmitz, A.,Yaguee Guillen, M. J.(2020).Are health e-mavens the new patient influencers?.Frontiers in Psychology,11,779.
  30. Dubois, E.,Blank, G.(2018).The echo chamber is overstated: the moderating effect of political interest and diverse media.Information, Communication & Society,21(5),729-745.
  31. Dubois, E.,Minaeian, S.,Paquet-Labelle, A.,Beaudry, S.(2020).Who to trust on social media: How opinion leaders and seekers avoid disinformation and echo chambers.Social Media + Society,6(2)
  32. Eckles, D.,Kizilcec, R. F.,Bakshy, E.(2016).Estimating peer effects in networks with peer encouragement designs.Proceedings of the National Academy of Sciences of the United States of America,113(27),7316-7322.
  33. Erdős, P.,Rényi, A.(1960).On the evolution of random graphs.Publication of The Mathematical Institute of the Hungarian Academy of Sciences,5,17-61.
  34. Flache, A.,Mäs, M.,Feliciani, T.,Chattoe-Brown, E.,Deffuant, G.,Huet, S.,Lorenz, J.(2017).Models of social influence: Towards the next frontiers.Journal of Artificial Societies and Social Simulation,20(4)
  35. Goel, S.,Anderson, A.,Hofman, J.,Watts, D. J.(2016).The structural virality of online diffusion.Management Science,62(1),180-196.
  36. Goldenberg, J.,Libai, B.,Muller, E.(2001).Talk of the network: A complex systems look at the underlying process of word-of-mouth.Marketing Letters,12(3),211-223.
  37. Golub, B.,Jackson, M. O.(2010).Naive learning in social networks and the wisdom of crowds.American Economic Journal-Microeconomics,2(1),112-149.
  38. Goncalves, B.,Perra, N.,Vespignani, A.(2011).Modeling users’ activity on twitter networks: validation of Dunbar’s number.PLoS One,6(8),e22656.
  39. Granovetter, M. S.(1973).The strength of weak ties.American Journal of Sociology,78(6),1360-1380.
  40. Grinberg, N.,Joseph, K.,Friedland, L.,Swire-Thompson, B.,Lazer, D.(2019).Fake news on Twitter during the 2016 US presidential election.Science,363(6425),374.
  41. Guess, A. M.,Nyhan, B.,Reifler, J.(2020).Exposure to untrustworthy websites in The 2016 US election.Nature Human Behaviour,4(5),472-480.
  42. Harrigan, N.,Achananuparp, P.,Lim, E.-P.(2012).Influentials, novelty, and social contagion.Social Networks,34(4),470-480.
  43. Haythornthwaite, C.(2002).Strong, weak, and latent Ties and the impact of new media.Information Society,18(5),385-401.
  44. Hegselmann, R.,Krause, U.(2015).Opinion dynamics under the influence of radical groups, charismatic leaders, and other constant signals: A simple unifying model.Networks and Heterogeneous Media,10(3),477-509.
  45. Huffaker, D.(2010).Dimensions of leadership and social influence in online communities.Human Communication Research,36(4),593-617.
  46. Hunter, R. F.,de la Haye, K.,Murray, J. M.,Badham, J.,Valente, T. W.,Clarke, M.,Kee, F.(2019).Social network interventions for health behaviours and outcomes: A systematic review and meta-analysis.Plos Medicine,16(9),e1002890.
  47. Huszti, E.,Albert, F.,Csizmady, A.,Nagy, I.,David, B.(2021).When spatial dimension matters: Comparing personal network characteristics in different segregated areas.Social Inclusion,9(4),375-387.
  48. Katz, E.,Lazarsfeld, P. F.(1955).Personal influence: the part played by people in The flow of mass communications.Free Press.
  49. Keijzer, M. A.,Corten, R.(2017).,未出版
  50. Keijzer, M. A.,Mäs, M.(2021).The strength of weak bots.Online Social Networks and Media,21
  51. Keijzer, M. A.,Mäs, M.,de Boer, V.(2022).The complex link between filter bubbles and opinion polarization.Data Science,5(2),139-166.
  52. Keijzer, M. A.,Mäs, M.,Flache, A.(2018).Communication in online social networks fosters cultural isolation.Complexity,2018,1-18.
  53. Laukemper, A. L., Keijzer, M.A., & Bakker, D.M. (2020). defSim (v0.1)[Computer Software]. In Available from https://github.com/defSim/defSim
  54. Liang, H.(2021).Decreasing social contagion effects in diffusion cascades: Modeling message spreading on social media.Telematics and Informatics,62
  55. Liang, H.(2018).Broadcast Versus Viral Spreading: The Structure of Diffusion Cascades and Selective Sharing on Social Media.Journal of Communication,68(3),525-546.
  56. Liang, H.,Fu, K.-w.(2019).Network Redundancy and Information Diffusion: The Impacts of Information Redundancy, Similarity, and Tie Strength.Communication Research,46(2),250-272.
  57. McPherson, M.,Smith-Lovin, L.,Cook, J. M.(2001).Birds of a Feather: Homophily in Social Networks.Annual Review of Sociology,27(1),415-444.
  58. Messing, S.,Westwood, S. J.(2014).Selective Exposure in the Age of Social Media: Endorsements Trump Partisan Source Affiliation When Selecting News Online.Communication Research,41(8),1042-1063.
  59. Mønsted, B.,Sapieżyński, P.,Ferrara, E.,Lehmann, S.(2017).Evidence of complex contagion of information in social media: An experiment using Twitter bots.PLoS One,12(9),e0184148.
  60. Nair, H. S.,Manchanda, P.,Bhatia, T.(2010).Asymmetric Social Interactions in Physician Prescription Behavior: The Role of Opinion Leaders.Journal of Marketing Research,47(5),883-895.
  61. Newman, M. E.,Strogatz, S. H.,Watts, D. J.(2001).Random graphs with arbitrary degree distributions and their applications.Physical Review E,64(2)
  62. Nickerson, R. S.(1998).Confirmation bias: A ubiquitous phenomenon in many guises.Review of general psychology,2(2),175-220.
  63. Peres, L. R.,Fontanari, J. F.(2010).The mass media destabilizes the cultural homogenous regime in Axelrod’s model.Journal of Physics A: Mathematical and Theoretical,43(5)
  64. Raghupathi, V.,Fogel, J.(2015).The Impact of Opinion Leadership on Purchases through Social Networking Websites.Journal of Theoretical and Applied Electronic Commerce Research,10(3),18-29.
  65. Reynolds, R. M.(2021).Diffusion in Information-Seeking Networks: Testing The Interaction of Network Hierarchy and Fluidity with Agent-Based Modeling.Communication Methods and Measures,15(4),292-311.
  66. Rolfe, M.(2014).Social networks and agent-based modelling.Analytical Sociology
  67. Ruths, D.(2019).The misinformation machine.Science,363(6425),348-348.
  68. Samuel-Azran, T.,Hayat, T.(2019).Online news recommendations credibility: The tie is mightier than the source.Comunicar,27(60),71-80.
  69. Sasahara, K.,Chen, W.,Peng, H.,Ciampaglia, G. L.,Flammini, A.,Menczer, F.(2021).Social influence and unfollowing accelerate the emergence of echo chambers.Journal of Computational Social Science,4(1),381-402.
  70. Schieb, C.,Preuss, M.(2018).Considering the Elaboration Likelihood Model for simulating hate and counter speech on Facebook.Studies in Communication and Media,7(4),580-606.
  71. Schulz, A.,Wirth, W.,Muller, P.(2020).We Are the People and You Are Fake News: A Social Identity Approach to Populist Citizens’ False Consensus and Hostile Media Perceptions.Communication Research,47(2),201-226.
  72. Shao, C.,Ciampaglia, G. L.,Varol, O.,Yang, K. C.,Flammini, A.,Menczer, F.(2018).The spread of low-credibility content by social bots.Nature Communications,9(1),4787.
  73. Sherif, M.,Hovland, C. I.(1961).Social judgment: Assimilation and contrast effects in communication and attitude change.Yale Univer. Press.
  74. Shibanai, Y.,Yasuno, S.,Ishiguro, I.(2001).Effects of Global Information Feedback on Diversity:Extensions to Axelrod’s Adaptive Culture Model.Journal of Conflict Resolution,45(1),80-96.
  75. Shin, J.,Thorson, K.(2017).Partisan selective sharing: The biased diffusion of fact-checking messages on social media.Journal of Communication,67(2),233-255.
  76. Sohn, D.(2022).Spiral of Silence in the Social Media Era: A Simulation Approach to the Interplay Between Social Networks and Mass Media.Communication Research,49(1),139-166.
  77. Ulloa, R.,Kacperski, C.,Sancho, F.(2016).Institutions and Cultural Diversity: Effects of Democratic and Propaganda Processes on Local Convergence and Global Diversity.PLoS One,11(4),e0153334.
  78. Van Bavel, J. J.,Harris, E. A.,Pärnamets, P.,Rathje, S.,Doell, K. C.,Tucker, J. A.(2021).Political psychology in the digital (mis) information age: A model of news belief and sharing.Social Issues and Policy Review,15,84-113.
  79. Vosoughi, S.,Roy, D.,Aral, S.(2018).The spread of true and false news online.Science,359(6380),1146-1151.
  80. Waterman, E. A.,Edwards, K. M.,Keyes, A. B.,Zulfiqar, H.,Banyard, V. L.,Valente, T. W.(2022).The stability of youth popular opinion leaders selected over time using social network analysis.American Journal of Community Psychology
  81. Watts, D. J.(2004).The "New" Science of Networks.Annual Review of Sociology,30(1),243-270.
  82. Watts, D. J.,Dodds, P. S.(2007).Influentials, networks, and public opinion formation.Journal of Consumer Research,34(4),441-458.
  83. Watts, D. J.,Strogatz, S. H.(1998).Collective dynamics of "small-world" networks.Nature,393(6684),440-442.
  84. Weeks, B. E.,Lane, D. S.,Kim, D. H.,Lee, S. S.,Kwak, N.(2017).Incidental exposure, selective exposure, and political information sharing: Integrating online exposure patterns and expression on social media.Journal of computer-mediated communication,22(6),363-379.
  85. Weimann, G.(1982).On the importance of marginality: One more step into the two-step flow of communication.American Sociological Review,47,764-773.
  86. Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. In Springer-Verlag New York. https://ggplot2.tidyverse.org
  87. Wischnewski, M.,Ngo, T.,Bernemann, R.,Jansen, M.,Krämer, N.(2022)."I agree with you, bot!" How users (dis)engage with social bots on Twitter.New Media & Society,14614448211072307.
  88. Wong, L. H.,Pattison, P.,Robins, G.(2006).A spatial model for social networks.Physica A: Statistical Mechanics and its Applications,360(1),99-120.
  89. Young, L. E.,Sidnam-Mauch, E.,Twyman, M.,Wang, L.,Xu, J. J.,Sargent, M.,Valente, T. W.,Ferrara, E.,Fulk, J.,Monge, P.(2021).Disrupting the COVID-19 Misinfodemic With Network Interventions: Network Solutions for Network Problems.American Journal of Public Health,111(3),514-519.
  90. Zhang, L.,Zhao, J.,Xu, K.(2016).Who creates Trends in Online Social Media: The Crowd or Opinion Leaders?.Journal of Computer-Mediated Communication,21(1),1-16.