댓글의 방향과 강도가 코로나19 관련 가짜뉴스 수용에 미치는 영향 : 체계적 정보처리의 매개효과 및 동조 성향의 조절효과 중심 분석
초록
이 연구의 목적은 코로나19 시기 가짜뉴스와 댓글이 결합하여 사회에 미치는 문제 상황을 배경으로, 코로나19 가짜뉴스 댓글의 방향과 강도가 가짜뉴스 메시지 수용, 가짜뉴스 행위 수용, 그리고 코로나19 예방행동의도에 미치는 영향을 분석하고, 이를 체계적 정보처리가 매개하는지와 동조 성향이 조절하는지를 알아보는 것이다. 이에 대해 이 연구는 2(방향: 찬성vs. 반대)*2(강도:강함vs. 약함) 피험자간 요인 설계를 구성해 총 4개의 메시지를 개발하고, 회귀 분석, 매개 분석, 조절효과 분석을 실시하였다. 연구 결과, 첫째, 코로나19 가짜뉴스 댓글의 방향은 메시지 수용에 유의한 정적 영향을 미치고, 행위 수용에 통계적으로 유의하지는 않지만 어느 정도 영향을 미치며, 댓글의 강도는 코로나19 예방행동의도에 통계적으로 유의하지는 않지만 어느 정도의 정적 영향을 미치는 것으로 나타났다. 둘째, 코로나19 댓글의 강도가 가짜뉴스 수용과 코로나19 예방행동의도에 미치는 영향을 체계적 정보처리가 통계적으로 유의하게 매개하였다. 셋째, 코로나19 가짜뉴스 댓글의 방향과 강도의 상호작용이 체계적 정보처리를 강화하여 가짜뉴스 수용에 미치는 영향에 대한 동조 성향의 조절된 매개효과는 나타나지 않았지만, 코로나19 댓글의 방향과 강도가 각각 체계적 정보처리를 강화하여 가짜뉴스 수용과 코로나19 예방행동의도에 미치는 영향에 대해 동조 성향의 조절효과가 나타났다. 구체적으로, 코로나19 가짜뉴스 댓글의 방향이 체계적 정보처리를 강화하여 가짜뉴스 메시지 수용, 행위 수용, 코로나19 예방행동의도에 미치는 영향은 동조 성향이 높은 사람에게만 유의미했고, 코로나19 가짜뉴스 댓글의 강도가 체계적 정보처리를 강화하여 가짜뉴스 메시지 수용, 행위 수용, 코로나19 예방행동의도에 미치는 영향은 동조 성향이 중간 수준인 사람과 높은 사람에게 유의미하게 나타났다. 이러한 연구결과를 바탕으로 커뮤니케이션의 주체인 언론과 뉴스 이용자에 대해 위험 커뮤니케이션 측면에서 정책적·실무적 제안점을 논의하였다.
Abstract
This study applied an empirical point of view to situations in which fake news and comments are combined to affect social reactions in the era of COVID-19. The purpose of the study is to investigate the effects of the direction and intensity of COVID-19 fake news comments on fake news acceptance–messages acceptance and behavior acceptance–and on COVID-19 preventive behavioral intention, and to figure out whether the effects are mediated by systematic information processing and moderated by the level of conformity. The present study adopted a 2(direction: agree vs. disagree)*2(intensity: strong vs. weak) experimental design and used a regression analysis to evaluate the impact of the direction and intensity of COVID-19 comments on the fake news acceptance with mediating and moderating effects of systematic information processing and the level of conformity. As the results of the study, the direction of COVID-19 fake news comments had a significant positive effect on fake news message acceptance and a marginally significant positive effect on behavior acceptance. The strength of COVID-19 fake news comments had a marginally significant effect on the COVID-19 preventive behavioral intentions. Second, systematic information processing mediated between the intensity of COVID-19 fake news comments and fake news acceptance, and between the intensity of COVID-19 fake news comments and COVID-19 preventive behavioral intentions in a statistically significant way. Third, the moderated mediating effect of the conformity level on the effect of the interaction between the direction and intensity of COVID-19 fake news comments on fake news acceptance through systematic information processing was not confirmed, but the moderating effect of the conformity level on the effects of the direction and intensity of COVID-19 comments on fake news acceptance and COVID-19 preventive behavioral intentions through systematic information processing was found respectively. Specifically, the moderating effect of the conformity level on the impacts of the direction of COVID-19 fake news comments on fake news acceptance and COVID-19 preventive behavioral intentions through systematic information processing was statistically significant among those who have a high level of conformity. Also, the moderating effect of the conformity level on the impacts of the intensity of COVID-19 fake news comments on fake news acceptance and COVID-19 preventive behavioral intentions through systematic information processing was statistically significant among those who have a medium and high level of conformity. Based on these findings, policy and practical implications were discussed in terms of risk communication for the media and news users who are the subjects of communication.
Keywords:
COVID-19, Fake News, Messages Acceptance, Systematic Information Processing, Conformity, Risk Communication키워드:
코로나19, 가짜뉴스, 댓글, 메시지 수용, 행위 수용, 예방행동의도, 체계적 정보처리, 동조 성향, 위험 커뮤니케이션References
- Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control (pp. 11-39). Berlin; Heidelberg: Springer. [https://doi.org/10.1007/978-3-642-69746-3_2]
- Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211-236. [https://doi.org/10.1257/jep.31.2.211]
- Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: Modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56, 101475. [https://doi.org/10.1016/j.tele.2020.101475]
- Baron, R. S., Vandello, J. A., & Brunsman, B. (1996). The forgotten variable in conformity research: Impact of task importance on social influence. Journal of Personality and Social Psychology, 71(5), 915-927. [https://doi.org/10.1037/0022-3514.71.5.915]
- Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15(4), 473-481. [https://doi.org/10.1086/209186]
- Bond, R., & Smith, P. B. (1996). Culture and conformity: A meta-analysis of studies using Asch’s (1952b, 1956) line judgment task. Psychological Bulletin, 119(1), 111. [https://doi.org/10.1037/0033-2909.119.1.111]
- Brosius, H.-B. (2003). Exemplars in the news: A theory of the effects of political communication. In J. Bryant, D. R. Ewoldsen, & J. Cantor (Eds.), Communication and emotion: Essays in honor of Dolf Zillmann (pp. 179-195). Mahwah, NJ: Lawrence Erlbaum.
- Chaiken, S. (1980). The heuristic model of persuasion. In M. Zanna, J. Olson, & C. Herman (Eds.), Social influence: The Ontario symposium (vol. 5, p. 339). Hillsdale, NJ: Lawrence Erlbaum Associates.
- Chaiken, S., Liberman, A., & Eagly, A. (1989). Heuristic and systematic processing within and beyond the persuasion context. In J. S. Veleman & J. A. Bargh (Eds.), Unintended thought (pp. 212-252). New York: Guilford.
- Chan, M. S., Jones, C. R., Jamieson, K. H., & Alberracin, D. (2017). Debunking: A meta-analysis of the psychological efficacy of messages countering misinformation. Psychological Science, 28(11), 1531-1546. [https://doi.org/10.1177/0956797617714579]
- Cho, K. (2007). A textual typological study of internet comments. Korean Rhetoric Society‧Korean Text Linguistics Fall Joint Academic Conference, Sungshin Women’s University, Seoul.
- Chun, W., & Kim, B. (2010). Effects of online comments on judgments of a politician: The role of correction messages. Korean Journal of Social and Personality Psychology, 24(2), 133-150. [https://doi.org/10.21193/kjspp.2010.24.2.008]
- Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591-621. [https://doi.org/10.1146/annurev.psych.55.090902.142015]
- Cohen, G. L. (2003). Party over policy: The dominating impact of group influence on political beliefs. Journal of Personality and Social Psychology, 85(5), 808-822. [https://doi.org/10.1037/0022-3514.85.5.808]
- Del Vicario, M. D., Bessi, A., Zollo, F., Petroni, F., Scala, A., Caldarelli, G., & Quattrociocchi, W. (2016). The spreading of misinformation online. Proc. Natl. Acad. Sci., 113(3), 554-559. [https://doi.org/10.1073/pnas.1517441113]
- Dong, S. Z., & Tam, L. L. (2013). Financial risk information processing in Hong Kong. Centre for Chines Media and Comparative Communication Research.
- Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117-140. [https://doi.org/10.1177/001872675400700202]
- French, J. R., & Raven. P. B. (1959). The bases of social power. In D. Cartwright (Ed.). Studies in social power (pp. 150-167). Ann Arbor, MI: Institute for Social Research.
- Gearhart, S., Moe, A., & Zhang, B. (2020). Hostile media bias on social media: Testing the effect of user comments on perceptions of news bias and credibility. Hum Behav & Emerg Tech, 2, 140-148. [https://doi.org/10.1002/hbe2.185]
- Griffin, R. J., Dunwoody, S., & Neuwirth, K. (1999). Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research, 80, 230-245. [https://doi.org/10.1006/enrs.1998.3940]
- Griffin, R. J., Dunwoody, S., & Yang, Z. J. (2012). 15 linking risk messages to information seeking and processing. Communication Yearbook, 36, 323. [https://doi.org/10.1080/23808985.2013.11679138]
- Griffin, R. J., Powell, M., Dunwoody, S., Neuwirth, K., Clark, D., & Novotny, V. (2004). Testing the robustness of a risk information processing model. In Annual Meeting of the Association for Education in Journalism and Mass Communication, Toronto, Canada.
- Griffin, R. J., Yang, Z., ter Huurne, E., Boerner, F., Ortiz, S., & Dunwoody, S. (2008). After the flood? Anger, attribution, and the seeking of information. Science Communication, 29(3), 285-315. [https://doi.org/10.1177/1075547007312309]
- Habermas, J. (1987). Eine art schadensabwicklung [A form of damage control]. Frankfurt am Main, Germany: Suhrkamp.
- Hennig-Thurau, T., Walsh, G., & Walsh, G. (2003). Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the internet. International Journal of Electronic Commerce, 8(2), 51-74. [https://doi.org/10.1080/10864415.2003.11044293]
- Houston, J. B., Hansen, G. J., & Nisbett, G. S. (2011). Influence of user comments on perceptions of media bias and third-person effect in online news. Electronic News, 5(2), 79-92. [https://doi.org/10.1177/1931243111407618]
- Huh, S., & Kim, Y. (2015). A comparative study on the application of RISP in the context of risk types – Focusing on typhoon and hydrofluoric acid spill risks. Korean Journal of Communication & Information, 70, 246-276.
- Humprecht, E., Hellmueller, L., & Lischka, J. A. (2020). Hostile emotions in news comments: A cross-national analysis of Facebook discussions. Social Media + Society, 6(1). [https://doi.org/10.1177/2056305120912481]
- Hwang, C. (2020). Fake news rhetoric. Seoul: Educational Science Press.
- Hwang, Y., & Kwon, O. (2017). A study on the conceptualization and regulation measures on fake news? Focused on self-regulation of internet service providers?. Journal of Media Law, Ethics and Policy Research, 16(1), 53-101. [https://doi.org/10.26542/JML.2017.4.16.1.53]
- Hyundai Economic Research Institute (2016). Estimating the economic cost of fake news and implications. Economic Commentary, 17(11).
- Jeong, I.-K., & Kim, Y.-S. (2006). Impact of "Datgeul" of online media on public opinion: An examination of perception of public opinion and third person effect. Korean Journal of Journalism & Communication Studies, 50(4), 302-327.
- Jeong, K. (2021). Special feature articles: Malicious comments, is regulation and blocking the best? A survey of perceptions of comments (‘Public opinion within public opinion’). Seoul: Korea Research.
- Johnson, B. K., Slater, M. D., Silver, N. A., & Ewoldsen, D. R. (2016). Entertainment and expanding boundaries of the self: Relief from the constraints of the everyday. Journal of Communication, 66(3), 386-408. [https://doi.org/10.1111/jcom.12228]
- Kelly, G., & Weeks, B. (2013). The promise and peril of real-time corrections to political misperceptions. Proceedings of the 2013 Conference on Computer Supported Cooperative Work (pp. 1047-1058), ACM, New York.
- Kenrick, D. T., Neuberg, S. L., & Cialdini, R. B. (2015). Social psychology: Unraveling the mystery (3rd ed.). Boston, NJ: Pearson.
- Kim, B.-C. (2004). A study on the effects of interactivity on discussion by internet newspaper users. Journal of Cybercommunication Academic Society, 14, 147-180.
- Kim, E. M., & Sun, Y. H. (2006). The effect of replies in internet news on the audience. Korean Journal of Journalism & Communication Studies, 50(4), 33-65.
- Kim, H.-J., Chong, E., Kim, E., Yang, S., Lee, J. W., & Kang, M. (2020). Fake news and fact check news differences : Focusing on news usage, perception, and literacy in multi-media environments. Korean Journal of Communication & Information, 101, 231-267. [https://doi.org/10.46407/kjci.2020.06.101.231]
- Kim, H. J., & Kim, K. (2016). Crisis communication strategy and public`s message acceptance –Mediating effects of responsibility attribution in the military collision situation. Journal of Public Relations Research, 20(2), 91-114. [https://doi.org/10.15814/jpr.2016.20.2.91]
- Kim, S. (2002, September). Article comments who writes and who reads. Newspaper & Broadcasting, 621, 8-11.
- Kim, S., Kim, W., Park, A., & Yang, J. (2018). Digital News Report 2018. Seoul: Korea Press Foundation.
- Kim, S., Na, K., & Cho, M. (2022, April 20). [Exclusive] Comments doubled due to Corona... “I judge”. Kukmin Ilbo, Retrieved 06/12/22 from http://news.kmib.co.kr/article/view.asp?arcid=0016995673&code=61121111&cp=nv
- Kim, S., & Oh, S. (2018b). Survey of Internet user perceptions of portal news services and comments. Media Issue, 4(5), Retrieved 11/02/23 from https://www.kpf.or.kr/synap/skin/doc.html?fn=BASE_201805310901199160.pdf&rs=/synap/result/upload/mediapds/
- Kim, S. J., & Kim, Y. (2019). The effects of cultural bias on climate change policy compliance and support : Mediating effects of risk perception, emotion, and efficacy. Korean Journal of Journalism & Communication Studies, 63(4), 230-274. [https://doi.org/10.20879/kjjcs.2019.63.4.007]
- Kim, Y. (2017). Domestic and foreign discussion trends and legal and institutional challenges related to fake news. Korean Journalism Law Association ‘Fake News and Media Environment Improvement Plan’ Seminar Proposal.
- Kim, Y.-W., & Yang, J.-E. (2009). The effect of cultural predictors on perceived ethicality of negotiation behavior: A comparison of ‘Chemyon’ and Hofstede’s cultural dimensions. Korean Journal of Communication & Information, 46, 212-244.
- Kongsompong, K., Green, R. T., & Patterson, P. G. (2009). Collectivism and social influence in the buying decision: A four-country study of inter- and intra-national differences. Australasian Marketing Journal, 17(3), 142-149. [https://doi.org/10.1016/j.ausmj.2009.05.013]
- Korea Centers for Disease Control and Prevention (2020, November 19). Code of conduct to prepare for the simultaneous outbreak of COVID-19 and influenza (general public). PR material.
- Ku, Y., Kim, H., & Noh, G. (2020). A study of how information processing influences preventive behavioral intention : Focusing on systematic and heuristic processing of particulate matter information. Journal of Public Relations Research, 24(2), 28-51.
- Lapinski, M. K., & Rimal, R. N. (2005). An explication of social norms. Communication Theory, 15(2), 127-147. [https://doi.org/10.1111/j.1468-2885.2005.tb00329.x]
- Larsen, K. S. (1990). The Asch conformity experiment: Replication and transhistorical comparison. Journal of Social Behavior and Personality, 5(4), 163.
- Lee, E.-J., & Jang, Y. (2009). Effects of others’ comments on internet news sites on perceptions of reality : Perceived public opinion, presumed media influence, and self-opinion. Korean Journal of Journalism & Communication Studies, 53(4), 50-71.
- Lee, I., & Kim, H. (2016). Effectiveness of online best reply on consumers’ perception of product quality- message sidedness, strength and consumer experience. Advertising Research, 110, 60-83. [https://doi.org/10.16914/ar.2016.110.60]
- Lee, J.-S. (2006). A longitudinal study examining factors meeting changes of attitudes towards technology use : Focusing on individuals’ subjective judgements and social influence of technology use. Korean Journal of Journalism & Communication Studies, 50(6), 388-414.
- Lee, S.-Y., & Park, J. (2020). A research on the effect of direction and social approval strength of best comments on attitudes toward online policy articles : Application of heuristic-systematic model. Korean Journal of Broadcasting and Telecommunication Studies, 34(6), 313-351.
- Lucas, T., Alexander, S., Firestone, I. J., & Baltes, B. B. (2006). Self‐efficacy and independence from social influence: Discovery of an efficacy–difficulty effect, Social Influence, 1(1), 58-80, [https://doi.org/10.1080/15534510500291662]
- MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation analysis. Annual Review of Psychology, 58, 593-614. [https://doi.org/10.1146/annurev.psych.58.110405.085542]
- Manning, M. J., & Romerstein, H. (2004). Historical dictionary of American propaganda (pp. 82-83). Westport, CT: Greenwood Press.
- Manosevitch, E., & Walker, D. (2009, April). Reader comments to online opinion journalism: A space of public deliberation. Paper presentation at the 10th International Symposium on Online Journalism, Austin, TX.
- 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. [https://doi.org/10.1177/0093650212466406]
- Min, H. M., & Choi, Y. J. (2017). The role of social conformity in rumor transmission : The influences of social conformity in online networks on rumor belief and rumor transmission. Broadcasting & Communacation, 18(4), 51-89.
- Na, E., & Lee, J. (2008). A study on comment culture: Changes in the use of online news and the meaning of public discourse. Korea Press Foundation Research Paper, 4.
- Newman, N., Fletcher, R., Schultz, A., Andi, S., & Nelsen, R. (2020). Digital News Report 2020. London, UK: Reuters Institute for the Study of Journalism.
- Noelle-Neumann, E. (1984). The spiral of silence: A response. In K. R. Sanders, L. L. Kaid, & D. Nimmo (Eds.), Political communication yearbook (pp. 66-94). Carbondale and Edwardsville, IL: Southern Illinois University Press.
- Noelle-Neumann, E. (1993). The spiral of silence: Public opinion-Our social skin. Chicago, IL: University of Chicago Press.
- Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32(2), 303-330. [https://doi.org/10.1007/s11109-010-9112-2]
- Oh, S., Jeong, S., & Park, A. (2017). Status and problems of the fake news. Seoul: Korea Press Foundation.
- Platow, M. J., Haslam, S. A., Both, A., Chew, I., Cuddon, M., Goharpey, N., & Grace, D. M. (2005). “It’s not funny when they’re laughing”: A self-categorization social-influence analysis of canned laughter. Journal of Experimental Social Psychology, 41, 542-550. [https://doi.org/10.1016/j.jesp.2004.09.005]
- Price, V., Nir, L., & Cappella, J. N. (2006). Normative and informational influences in online political discussions. Communication Theory, 16(1), 47-74. [https://doi.org/10.1111/j.1468-2885.2006.00005.x]
- Roberts, C. (2010). Correlations among variables in message and messenger credibility scales. American Behavioral Scientist, 54(1), 43-56. [https://doi.org/10.1177/0002764210376310]
- Roh, S., Choi, J., & Min, Y. (2017). Correlates of fake news effects : Identifying facilitating and constraining factors on fake news exposure and acceptance in the 2017 Korean presidential election. Journal of Cybercommunication Academic Society, 34(4), 99-149.
- Savigny, H. (2002). Public opinion, political communication and the internet. Politics, 22, 1-8. [https://doi.org/10.1111/1467-9256.00152]
- Scheufele, D. A., & Moy, P. (2000). Twenty-five years of the spiral of silence: A conceptual review and empirical outlook. International Journal of Public Opinion Research, 12, 3-28. [https://doi.org/10.1093/ijpor/12.1.3]
- Seo, M. (2016). Effects of risk information seeking and processing on MERS preventive behaviors and moderating roles of SNS use during 2015 MERS outbreak in Korea. Korean Journal of Communication & Information, 78, 116-140.
- Shim, J., Cho, C., Yang, H., Ahn, I., & Na, E. (2006). Internet usage status of netizens in the era of web 2.0. 2006 Internet Issues In-depth Survey Report, Korea Internet & Security Agency.
- Smith, R. C. (2019). Fake news, French law and democratic legitimacy: Lessons for the United Kingdom?. Journal of Media Law, 11(1), 52-81. [https://doi.org/10.1080/17577632.2019.1679424]
- Sohn, S., Lee, G., Hong, J., Cho. J., & Jeong, E. (2018). How does Twitter distribute fake news? - Analysis of distribution patterns, influencers, and frequently-used words of ‘traffic regulation amendment’ and ‘September 9th war in Korean peninsula’ news-. Journal of Cybercommunication Academic Society, 35(4), 203-251. [https://doi.org/10.36494/JCAS.2018.12.35.4.203]
- Southwell, B. G., Thorson, E. A., & Sheble, L. (2018). Misinformation among mass audiences as a focus for inquiry. In B. G. Southwell, E. A. Thorson, & L. Sheble (Eds.), Misinformation and mass audiences (pp. 1-11). Austin, TX: University of Texas Press. [https://doi.org/10.7560/314555]
- Sundar, S. S., Knobloch-Westerwick, S., & Hastall, M. R. (2007). News cues: Information scent and cognitive heuristics. Journal of the American Society for Information Science and Technology, 58(3), 366-378. [https://doi.org/10.1002/asi.20511]
- Sunstein, C. R. (2009). On rumors: How falsehoods spread, why we believe them, what can be done. New York: Farrar, Straus and Giroux.
- Swire, B., Berinsky, A. J., Lewandowsky, S., & Ecker, U. K. H. (2017). Processing political misinformation: Comprehending the trump phenomenon. Royal Society Open Science, 4(3), 160802. [https://doi.org/10.1098/rsos.160802]
- Tandoc, E. C. Jr., Lim, Z. W., & Ling, R. (2018). Defining “Fake news”. Digital Journalism, 6(2), 137-153. [https://doi.org/10.1080/21670811.2017.1360143]
- Thorson, K., Vraga, E., & Ekdale, B. (2010). Credibility in context: How uncivil online commentary affects news credibility. Mass Communication and Society, 13, 289-313. [https://doi.org/10.1080/15205430903225571]
- Trumbo, C. W. (2002). Information processing and risk perception: An adaptation of the heuristic-systematic model. Journal of Communicationm, 52(2), 367-382. [https://doi.org/10.1111/j.1460-2466.2002.tb02550.x]
- Tsikerdekis, M. (2013). The effects of perceived anonymity and anonymity states on conformity and groupthink in online communities: A Wikipedia study. Journal of the American Society for Information Science and Technology, 64(5), 1001-1015. [https://doi.org/10.1002/asi.22795]
- Vasoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146-1151. [https://doi.org/10.1126/science.aap9559]
- Walther, J. B., DeAndrea, D., Kim, J., & Anthony, J. C. (2010). The influence of online comments on perceptions of antimarijuana public service announcements on YouTube. Human Communication Research, 36, 469-492. [https://doi.org/10.1111/j.1468-2958.2010.01384.x]
- White, R. W. (1959). Motivation reconsidered: The concept of competence. Psychological Review, 66(5), 297-333. [https://doi.org/10.1037/h0040934]
- Wooten, D. B., & Reed, A. II. (1998). Informational influence and the ambiguity of product experience: Order effects on the weighting of evidence. Journal of Consumer Psychology, 7(1), 79-99. [https://doi.org/10.1207/s15327663jcp0701_04]
- Yanagi, Y., Orihara, R., Sei, Y., Tahara, Y., & Ohsuga, A. (2020). Fake news detection with generated comments for news articles. 2020 IEEE 24th International Conference on Intelligent Engineering Systems(INES), 85-90. [https://doi.org/10.1109/INES49302.2020.9147195]
- Yang, H. S. (2008). The effects of the opinion and quality of user postings on internet news readers’ attitude toward the news issue. Korean Journal of Journalism & Communication Studies, 52(2), 254-281.
- Yang, Z. J., & Kahlor, L. (2013). What, me worry? The role of affect in information seeking and avoidance. Science Communication, 35(2), 189-212. [https://doi.org/10.1177/1075547012441873]
- Yum, J.-Y., Kim, R., & Jeong, S.-H. (2020). A meta-analysis of the effects of user comments. Journal of Communication Research, 57(2), 5-49.
- Yum, J.-Y., & Jeong, S.-H. (2018). Research on fake news perception and fact-checking effect– Role of prior-belief consistency. Korean Journal of Journalism & Communication Studies, 62(2), 41-80. [https://doi.org/10.20879/kjjcs.2018.62.2.002]