Asia pacific journal of information systems

  • 제29권4호
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  • Pages.591-614
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  • 2019
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  • 2288-5404(pISSN)
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  • 2288-6818(eISSN)
한국경영정보학회 (The Korea Society of Management Information Systems)
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Why Do People Spread Online Rumors? An Empirical Study

  • Jong-Hyun Kim (Fintech investment team, Korea Investment Partners Co.) ;
  • Gee-Woo Bock (Business School, Sungkyunkwan University) ;
  • Rajiv Sabherwal (Sam M. Walton College of Business, University of Arkansas) ;
  • Han-Min Kim (Business School, Sungkyunkwan University)
  • 투고 : 2019.03.21
  • 심사 : 2019.07.15
  • 발행 : 2019.12.31
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⟨ 이전 논문 다음 논문 ⟩

초록

With the proliferation of social media, it has become easier for people to spread rumors online, which can aggravate the issues arising from online rumors. There are many individuals and organizations that are adversely affected by malicious online rumors. Despite their importance, there has been little research into why and how people spread rumors online, thus inhibiting the understanding of factors that affect the spreading of online rumors. With attention seeking to address this gap, this paper draws upon the dual process theory and the de-individuation theory to develop a theoretical model of factors affecting the spreading of an online rumor, and then empirically tests it using survey data from 211 individuals about a specific rumor. The results indicate that the perceived credibility of the rumor affects the individuals' attitudes toward spreading it, which consequently affects the rumor spreading behavior. Vividness, confirmation of prior beliefs, argument strength, and source credibility positively influence the perceived credibility of online rumors. Finally, anonymity moderates the relationship between attitude toward spreading online rumors and the spreading behavior.

키워드

과제정보

This work was supported by Samsung Research Fund [2008-0458-000].

참고문헌

  1. Abbott, K., and Makowsky, W. (2010). Korean pop star battles attacks on stanford record. accessed Stanford Daily on Sept 28, 2010, Retrieved from http://www.stanforddaily.com/2010/09/27/korean-pop-star-battles-attacks-on-stanford-record/.
  2. Agarwal, R., Gupta, A., and Kraut, R. (2008). The interplay between digital and social networks. Information Systems Research, 19(3), 243-252. https://doi.org/10.1287/isre.1080.0200
  3. Alba, J., and Hutchinson, J. (1987). Dimensions of consumer expertise. Journal of Consumer Research, 13, 411-454. https://doi.org/10.1086/209080
  4. Ambrosini, P. J. (1983). Clinical assessment of group and defensive aspects of rumor. International Journal of Group Psychotherapy, 33, 69-83. https://doi.org/10.1080/00207284.1983.11491745
  5. Anderson, J. R. (1995). Cognitive psychology and its implications, Fourth edition. NY: Freeman.
  6. Ashkanasy, N. M., Humphrey, R. H., and Quy, N. H. (2017). Integrating emotions and affect in theories of management. Academy of Management Review, 42(2), 175-189. https://doi.org/10.5465/amr.2016.0474
  7. Baddeley, A. D. (1982). Your memory, a user's guide. NY: Macmillan.
  8. Bird, D. A. (1979). Rumor as folklore: An interpretation and inventory. Doctoral Dissertation, Indiana University, Bloomington.
  9. Blake, R. H., McFaul, T. R., and Porter, W. H. (1974). Authority and mass media as variables in rumor transmission. Paper presented at the annual meeting of the Western Speech Communication Association, Newport Beach, CA.
  10. Brandtzaeg, P. B., and Folstad, A. (2017). Trust and distrust in online fact-checking services. Communications of the ACM, 60(9), 65-71. https://doi.org/10.1145/3122803
  11. Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185-216. https://doi.org/10.1177/135910457000100301
  12. Brucks, M. (1985). The effect of product class knowledge on information search behavior. Journal of Consumer Research, 12(1), 1-16. https://doi.org/10.1086/209031
  13. Burbules, N. C. (1998). Rhetorics of the web: Hyper-reading and critical literacy. In I. Snyder (Ed.), Page to screen: Taking literacy into the electronic era (pp. 102-122). London: Routledge.
  14. Cacioppo, J. T., Petty, R. E., and Morris, K. J. (1983). Effects of need for cognition on message evaluation, recall, and persuasion. Journal of Personality and Social Psychology, 45(4), 805-818. https://doi.org/10.1037/0022-3514.45.4.805
  15. Castillo, C., Mendoza, M., and Poblete, B. (2011). Information credibility on Twitter. Proceedings of World Wide Web Conference, Hyderabad, India.
  16. Chaiken, S. (1987). The Heuristic Model of Persuasion. In M.P. Zanna, J.M. Olson and C.P. Herman (Eds.), Social influence: The Ontario Symposium (pp. 3-39). Hillsdale, NJ: Erlbaum.
  17. Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7-16.
  18. Cho, D., and Kim, S. (2012). Empirical analysis of online anonymity and user behaviors: The impact of real name policy. Proceedings of the 45th Hawaii International Conference on System Sciences (pp. 3041-3050). Maui, HI, USA.
  19. Chua, A. Y., and Banerjee, S. (2018). Intentions to trust and share online health rumors: An experiment with medical professionals. Computers in Human Behavior, 87, 1-9. https://doi.org/10.1016/j.chb.2018.05.021
  20. Cindy Man-Yee, C., Sia, C. L., and Kuan, K.Y. (2012). Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. Journal of the Association for Information Systems, 13(8), 618-635. https://doi.org/10.17705/1jais.00305
  21. Cheung, M. Y., Luo, C., Sia, C. L., and Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13(4), 9-38. https://doi.org/10.2753/JEC1086-4415130402
  22. Connolly, T., Jessup, L. M., and Valacich, J. S. (1990). Effects of anonymity and evaluative tone on idea generation in computer-mediated groups. Management Science, 36(6), 689-703. https://doi.org/10.1287/mnsc.36.6.689
  23. Deutsch, M., and Gerrard, H. B. (1955). A study of normative and informational social influence upon individual judgment. Journal of Abnormal and Social Psychology, 53(3), 629-636. https://doi.org/10.1037/h0046408
  24. DiFonzo, N., and Bordia, P. (2007). Rumor psychology: Social and organizational approaches. American Psychological Association. NY: Hamilton Printing.
  25. Eagly, A., and Chaiken. H. (1993). Psychology of attitudes. NY: Harcourt Brace Jovanovich.
  26. Esposito, J. L. (1986). Subjective factors and rumor transmission: A field investigation of the influence of anxiety, importance, and belief on rumormongering. Doctoral Dissertation, Temple University, Dissertation Abstracts International, 48, 596B.
  27. Fishbein, M., and Ajzen, I. (1975). Beliefs, attitude, intention and behavior: an introduction to theory and research. MA: Addison-Wesley Publishing Company.
  28. Fogg, B. J., Marshall, J., Laraki, O., Osipovich, A., Varma, C., Fang, N., Paul, J., Rangnekar, A., Shon, J., Swani, P., and Treinen, M. (2001). What makes websites credible? A report on a large quantitative study. In J.A. Nicholas and M.L. Schneider (eds.), Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 61-68). NY: ACM Press.
  29. Fornell, C., and Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440-452.
  30. Fornell, C., and Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  31. Habermas, J. (1984). The Theory of Communicative Action, McCarthy, T. (trans.). MA: Beacon Press.
  32. Hovland, C. I., and Weiss, W. (1951). The influence of source credibility on communication effectiveness. Public opinion quarterly, 15(4), 635-650. https://doi.org/10.1086/266350
  33. Hovland, C. I., Janis, I. L., and Kelley, J. J. (1953). Communication and persuasion. New Haven, CT: Yale University Press.
  34. Jaeger, M. E., Anthony, S., and Rosnow, R. L. (1980). Who hears what from whom and with what effect: A study of rumor. Personality and Social Psychology Bulletin, 6, 473-478. https://doi.org/10.1177/014616728063024
  35. Jessup, L. M., Connolly, T., and Galegher, J. (1990). The effects of anonymity on gdss group process in automated group problem solving. MIS Quarterly, 14(3), 312-321.
  36. Jingjun, X., Benbasat, I., and Cenfetelli, R. (2011). The effects of service and consumer product knowledge on online customer loyalty. Journal of the Association for Information Systems, 12(11), 741-766. https://doi.org/10.17705/1jais.00279
  37. Jong, W., and Duckers, M. L. (2016). Self-correcting mechanisms and echo-effects in social media: An analysis of the "gunman in the newsroom" crisis. Computers in Human Behavior, 59, 334-341. https://doi.org/10.1016/j.chb.2016.02.032
  38. Johnson, E., and Russo, J. (1984). Product familiarity and learning new information. Journal of Consumer Research, 11(1), 542-550. https://doi.org/10.1086/208990
  39. Kaplan, M., and Miller, C. (1987). Group decision making and normative versus informational influence: Effects of type of issue and assigned decision role. Journal of Personality and Social Psychology, 53, 306-313. https://doi.org/10.1037/0022-3514.53.2.306
  40. Kelley, H. H. (1967). Attribution theory in social psychology. In D. Levine (Ed.), Nebraska Symposium on Motivation (pp. 192-238). Lincoln: University of Nebraska Press.
  41. Kelly, S. R. (2004). Rumors in Iraq: A guide to winning hearts and minds. Master's thesis, Naval Postgraduate School, Monterey, CA. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.165.3225&rep=rep1&type=pdf.
  42. Kiesler, S., Siegel, J., and McGuire, T. W. (1984). Social psychological aspects of computer-mediated communication. American Psychologist, 9, 1123-1134. https://doi.org/10.1037/0003-066X.39.10.1123
  43. Kim, D., and Benbasat, I. (2009). Trust-assuring arguments in B2C e-commerce: Impact of content, source, and price on trust. Journal of Management Information Systems, 26(3), 175-206. https://doi.org/10.2753/MIS0742-1222260306
  44. Kim, J. H., and Bock, G. W. (2011, July). A study on the factors affecting the behavior of spreading online rumors: Focusing on the rumor recipient's emotions. In PACIS (p. 98).
  45. Kimmel, A. J., and Keefer, R. (1991). Psychological correlates of the transmission and acceptance of rumors about AIDS. Journal of Applied Social Psychology, 21, 1608-1628.
  46. Kimmel, A. J. (2004). Ethical trends in psychology and marketing research: an update. Paper Presented at the 112th Annual APA Convention, Honolulu, HI.
  47. Kleinsmith, L. J., and Kaplan, S. (1963). Paired associate learning as a function of arousal and interpolated interval. Journal of Experimental Psychology, 65, 190-193. https://doi.org/10.1037/h0040288
  48. Kwan, S., Cha, M., Jung, K., Chen, W., and Wang, Y. (2013). Prominent features of rumor propagation in online social media. Proceedings of the 18th International World Wide Web Conference, Dallas, TX, USA.
  49. LeBar, K. S., and Phelps, E. A. (1998). Arousal-mediated memory consolidation: the role of the medial temporal lobe in humans. Psychological Science, 9(6), 490-493. https://doi.org/10.1111/1467-9280.00090
  50. Liu, L., Qi, J., and Yu, C. (2013). How does praise and rumor spread online? Analyzing user relationships on social networks: A case study of Haidliao. Proceedings of 20th International Conference on Management Science and Engineering (pp. 57-65). Harbin, China.
  51. Lohmoller, J. (1989). Latent variable path modelling with partial least squares. Heidelberg: Physica-Verlag.
  52. Lord, C. G., Ross, L., and Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37, 2098-2109. https://doi.org/10.1037/0022-3514.37.11.2098
  53. Lowry, P. B., Zhang, J., Wang, C., and Siponen, M. (2016). Why do adults engage in cyberbullying on social media? An integration of online disinhibition and deindividuation effects with the social structure and social learning model. Information Systems Research, 27(4), 962-986. https://doi.org/10.1287/isre.2016.0671
  54. Luo, C., Cheung, M., Sia, C. L., and Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13(4), 9-38.
  55. Ma, M., and Agarwal, R. (2007). Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities. Information Systems Research, 18, 42-67. https://doi.org/10.1287/isre.1070.0113
  56. Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D., and McCann, R. (2003). Bringing the concept of credibility into the 21st century: Integrating perspectives on source, message, and media credibility in the contemporary media environment. Communication Yearbook, 27, 293-335. https://doi.org/10.1207/s15567419cy2701_10
  57. Moore, M. J., Nakano, T., Enomoto, A., and Suda, T. (2012). Anonymity and roles associated with aggressive posts in an online forum. Computers in Human Behavior, 28(3), 861-867. https://doi.org/10.1016/j.chb.2011.12.005
  58. Nabi, R. L., and Hendriks, A. (2003). The Persuasive effect of host and audience reaction shots in television talk shows. Journal of Communication, 53(3), 527-543. https://doi.org/10.1111/j.1460-2466.2003.tb02606.x
  59. Nisbett, R., and Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Englewood Cliffs, NJ: Prentice-Hall, Inc.
  60. Oh, O., Agrawal, M., and Rao, H. R. (2013). Community intelligence and social media services: A rumor theoretic analysis of tweets during social crises. Mis Quarterly, 37(2), 407-426. https://doi.org/10.25300/MISQ/2013/37.2.05
  61. O'Keefe, D. J. (2002). Persuasion: Theory and research. Thousand Oaks, CA: Sage.
  62. Pavlou, P. A., Liang, H., and Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS quarterly, 31(1), 105-136. https://doi.org/10.2307/25148783
  63. Petty, R. E., and Cacioppo, J.T. (1981). Attitudes and persuasion: Classic and contemporary approaches. Dubuque, IA: Brown.
  64. Pincus, S., and Waters, L. K. (1977). Informational social influence and product quality judgments. Journal of Applied Psychology, 5(62), 615-619. https://doi.org/10.1037/0021-9010.62.5.615
  65. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., and Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. https://doi.org/10.1037/0021-9010.88.5.879
  66. Podsakoff, P. M., MacKenzie, S. B., and Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539-569. https://doi.org/10.1146/annurev-psych-120710-100452
  67. Rosnow, R. L., Yost, J. H., and Esposito, J. L. (1986). Belief in Rumor and Likelihood of Rumor Transmission. Language and Communication, 6, 189-194. https://doi.org/10.1016/0271-5309(86)90022-4
  68. Rudell, F. (1979). Consumer food selection and nutrition information. NY: Praeger.
  69. Scheper-hughes, N. (1990). Three propositions for a critically applied medical anthropology. Social Science and Medicine, 30, 189-197. https://doi.org/10.1016/0277-9536(90)90079-8
  70. Schiffman, L. G., and Kanuk, L. L. (2004). Consumer behavior. Prentice Hall, 250-287.
  71. Scott, C. R. (1998). To reveal or not to reveal: A theoretical model of anonymous communication. Communication Theory, 8(4), 381-407. https://doi.org/10.1111/j.1468-2885.1998.tb00223.x
  72. Sia, C. L., Tan, B. C. Y., and Wei, K. K. (2002). Group polarization and computer-mediated communication: Effects of communication cues, social presence, and anonymity. Information Systems Research, 13(1), 70-90. https://doi.org/10.1287/isre.13.1.70.92
  73. Smith, R. E., and Vogt, C. A. (1995). The effects of integrating advertising and negative word of mouth communications on message processing and response. Journal of Consumer Psychology, 4(2), 133-152. https://doi.org/10.1207/s15327663jcp0402_03
  74. Spears, R., Postmes, T., Lea, M., and Wolbert, A. (2002). When are net effects gross products? The power of influence and the influence of power in computer-mediated communication. Journal of Sociology, 58(1), 91-107.
  75. Sproull, L., and Kiesler, S. (1991). Connections: New ways of working in the networked organization. Cambridge, MA: MIT Press.
  76. Steuer, J. (1992). Defining virtual reality: Dimensions determining tele-presence. Journal of Communication, 42(4), 73-93.
  77. Sundar, S. S. (2008). The main model: A heuristic approach to understanding technology effects on credibility. In M. J. Metzger and A. J. Flanagin (Eds.), Digital Media, Youth and Credibility (pp. 73-100). Cambridge, MA: The MIT Press.
  78. Thomas, S. A. (2007). Lies, damn lies, and rumors: an analysis of collective efficacy, rumors, and fears in the wake of Katrina. Sociology Spectrum, 27, 679-703. https://doi.org/10.1080/02732170701534200
  79. Tian, R. Y. and Chen, Z. L. (2013). Advances in intervention of online public opinion. Social Physics Series, Beijing, Science Press.
  80. Walthen, C. N., and Burkell, J. (2002). Believe it or not: Factors influencing credibility on the web. Journal of the American Society for Information Science and Technology, 53(2), 134-144. https://doi.org/10.1002/asi.10016
  81. Wasko M., and Faraj, S. (2005). Why should i share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1), 35-58. https://doi.org/10.2307/25148667
  82. Weiner, B. (2000). Intrapersonal and interpersonal theories of motivation from an attributional perspective. Educational Psychology Review, 12, 1-14. https://doi.org/10.1023/A:1009017532121
  83. Zeff, R. L., and Aronson, B. (1997). Advertising on the internet. NY: Wiley Inc.
  84. Zhang, W., and Watts, S. (2003). Knowledge adoption in online communities of practice. In S. T. March, A. Massey, and J. I. DeGross (eds.), 24th International Conference on Information Systems (pp. 96-109). Atlanta: AIS.
  85. Zhao, L., Wang, Q., Cheng, J., Chen, Y., Wang, J., and Huang, W. (2011). Rumor spreading model with consideration of forgetting mechanism: A case of online blogging live journal. Physica A, 390(13), 2619-2625. https://doi.org/10.1016/j.physa.2011.03.010