Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing
Fake news swiftly spreads throughout social media platforms, influencing public opinion, decision-making, and even societal cohesion. Understanding the elements which drive the dissemination of fake news has become an important and pressing issue in the contemporary digital environment. Through a detailed examination of data obtained from 328 young individuals, the research identifies para-social interaction, information seeking, information sharing, and status-seeking as the main driving factors for the transmission of fake news in the digital era. Conversely, the factors of passing time and fear of missing out were found to have a negligible relationship with fake news sharing, indicating a lesser impact on the spread of fake news. Additionally, the model fit as evaluated by R-square, suggested that approximately 55% of the variance in fake news sharing was explained by the independent variables included in the study. The findings of the study will help devise effective strategies to counteract the phenomenon of fake news sharing and promote media literacy.
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Fake News Sharing, Parasocial Interaction, Information Sharing, Information Seeking, Status- Seeking, Pass time, Fear of Missing Out (FoMO)
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(1) Maryam Nadeem
Undergraduate Scholar (BS Mass Communication), Department of Mass Communication, Government College University, Faisalabad, Punjab, Pakistan.
(2) Muhammad Usman Aslam
Undergraduate Scholar (BS Mass Communication), Department of Mass Communication, Government College University, Faisalabad, Punjab, Pakistan.
(3) Sobia Shahzad
Assistant Professor, Department of Mass Communication, Government College University, Faisalabad, Punjab, Pakistan.
- Ahmed, S. (2022). Disinformation Sharing Thrives with Fear of Missing Out among Low Cognitive News Users: A Cross-national Examination of Intentional Sharing of Deep Fakes. Journal of Broadcasting & Electronic Media, 66(1), 89–109. https://doi.org/10.1080/08838151.2022.2034826
- 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. (2020). Modelling the antecedent factors that affect online fake news sharing on COVID-19: the moderating role of fake news knowledge. Health Education Research, 35(5), 490–503. https://doi.org/10.1093/her/cyaa030
- Bode, L., & Vraga, E. K. (2015). In related news, that was wrong: the correction of misinformation through related stories functionality in social media. Journal of Communication, 65(4), 619– 638. https://doi.org/10.1111/jcom.12166
- Bruns, A., & Highfield, T. (2015). Is Habermas on Twitter?: Social media and the public sphere. In The Routledge Companion to Social Media and Politics (pp. 56-73). Routledge.
- Bakshy, E., Messing, S., & Adamic, L. A. (2015). Political science. Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. https://doi.org/10.1126/science.aaa1160
- Cheng, J., & Schäfer, M. S. (2020). The social media logic of political misinformation. The International Journal of Press/Politics, 25(3), 332-348.
- Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annu. Rev. Psychol., 55, 591-621.
- Cialdini, R. B. (2009). Influence: Science and practice (Vol. 4). Boston, MA: Pearson education.
- 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 of the United States of America, 113(3), 554–559. https://doi.org/10.1073/pnas.1517441113
- Egelhofer, J. L., & Lecheler, S. (2019). Fake news as a two-dimensional phenomenon: a framework and research agenda. Annals of the International Communication Association, 43(2), 97–116. https://doi.org/10.1080/23808985.2019.1602782
- Fletcher, R., & Nielsen, R. K. (2017). Are news audiences increasingly fragmented? A Cross- National Comparative Analysis of Cross- Platform News Audience Fragmentation and Duplication. Journal of Communication, 67(4), 476–498. https://doi.org/10.1111/jcom.12315
- Gelfert, A. (2018). Fake news: A definition. Informal logic, 38(1), 84-117. http://dx.doi.org/10.22329/il.v38i1.5068
- uess, A. M., Nagler, J., & Tucker, J. A. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science Advances, 5(1). https://doi.org/10.1126/sciadv.aau4586
- Guess, A.M., Nyhan, B., & Reifler, J. (2018). Selective exposure to misinformation: Evidence from the consumption of fake news during the 2016 US presidential campaign. https://www.american.edu/spa/ccps/politics-of-truth/upload/nyhan-american.pdf
- Guess, A. M., Nyhan, B., & Reifler, J. (2020). Exposure to untrustworthy websites in the 2016 US election. Nature human behaviour, 4(5), 472-480. https://doi.org/10.1038%2Fs41562-020-0833-x
- Handarkho, Y. D. (2020). Impact of social experience on customer purchase decision in the social commerce context. Journal of Systems and Information Technology, 22(1), 47–71. https://doi.org/10.1108/jsit-05-2019-0088
- Hao, K., & Heaven, W. D. (2020). The year deepfakes went mainstream. MIT Technology Review. Retrieved, 4(25), 2021. https://www.technologyreview.com/2020/12/2 4/1015380/best-ai-deepfakes-of-2020
- Iyengar, S., & Hahn, K. S. (2009). Red media, blue media: Evidence of ideological selectivity in media use. Journal of Communication, 59(1), 19- 39. https://psycnet.apa.org/doi/10.1111/j.1460-2466.2008.01402.x
- Kim, A., & Dennis, A. R. (2019). Says who? The effects of presentation format and source rating on fake news in social media. Mis quarterly, 43(3), 1025-1039. http://dx.doi.org/10.25300/MISQ/2019/15188
- Knobloch-Westerwick, S., Johnson, B. K., & Westerwick, A. (2015). Confirmation bias. In The international encyclopedia of interpersonal communication (pp. 1-11). John Wiley & Sons, Inc.
- Larson, H., De Figueiredo, A., Zhao, X., Schulz, W., Verger, P., Johnston, I. G., Cook, A. R., & Jones, N. (2016). The State of Vaccine Confidence 2016: Global Insights through a 67-Country survey. EBioMedicine, 12, 295–301. https://doi.org/10.1016/j.ebiom.2016.08.042
- Lazer, D., Baum, M., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., Schudson, M., Sloman, S. A., Sunstein, C. R., Thorson, E., Watts, D. J., & Zittrain, J. (2018). The science of fake news. Science, 359(6380), 1094–1096. https://doi.org/10.1126/science.aao2998
- Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and Its Correction: Continued Influence and Successful Debiasing. Psychological Science in the Public Interest, 13(3), 106–131. http://www.jstor.org/stable/23484653
- Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017). Beyond misinformation: Understanding and coping with the “post-truth†era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369. https://doi.org/10.1016/j.jarmac.2017.07.008
- Maheshwari, S. (2016). How fake news goes viral: A case study. The New York Times, 20. https://www.nytimes.com/2016/11/20/business/media/how-fake-news-spreads.html
- Munson, S. A., & Resnick, P. (2010). Presenting diverse political opinions: How and how much. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1457- 1466). http://dx.doi.org/10.1145/1753326.1753543
- Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32(2), 303- 330. http://dx.doi.org/10.1007/s11109-010-9112-2
- Pennycook, G., Bear, A., Collins, E. T., & Rand, D. G. (2020). The implied truth effect: Attaching warnings to a subset of fake news headlines increases perceived accuracy of headlines without warnings. Management Science, 66(11), 4944-4957. http://dx.doi.org/10.1287/mnsc.2019.3478
- Pennycook, G., & Rand, D. G. (2021). The psychology of fake news. Trends in Cognitive Sciences, 25(5), 388–402. https://doi.org/10.1016/j.tics.2021.02.007
- Pennycook, G. (2019). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition, 188, 39–50. https://doi.org/10.1016/j.cognition.2018.06.011
- Pennycook, G., & Rand, D. G. (2019). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, 116(7), 2521-2526. https://doi.org/10.1073/pnas.1806781116
- 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. http://dx.doi.org/10.1111/jcom.12284
- Tsai, W. H. S., & Men, L. R. (2017). Social CEOs: The effects of CEOs’ communication styles and parasocial interaction on social networking sites. New media & society, 19(11), 1848-1867. http://dx.doi.org/10.1177/1461444816643922
- Vosoughi, 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
- Vraga, E. K., & Tully, M. (2019). “I Don't Trust Themâ€: The Influence of Para-Social Interaction and Source Cues on Fake News Perceptions. Journal of Computer-Mediated Communication, 24(3), 107-124.
- Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policymaking (Vol. 27, pp. 1-107). Strasbourg: Council of Europe. https://rm.coe.int/information-disorder-toward-an-interdisciplinary-framework-for-researc/168076277c
- Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., & Procter, R. (2018). Detection and resolution of rumours in social media: A survey. ACM Computing Surveys (CSUR), 51(2), 1-36. http://dx.doi.org/10.1145/3161603
Cite this article
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APA : Nadeem, M., Aslam, M. U., & Shahzad, S. (2023). Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing. Global Sociological Review, VIII(I), 211-220. https://doi.org/10.31703/gsr.2023(VIII-I).20
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CHICAGO : Nadeem, Maryam, Muhammad Usman Aslam, and Sobia Shahzad. 2023. "Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing." Global Sociological Review, VIII (I): 211-220 doi: 10.31703/gsr.2023(VIII-I).20
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HARVARD : NADEEM, M., ASLAM, M. U. & SHAHZAD, S. 2023. Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing. Global Sociological Review, VIII, 211-220.
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MHRA : Nadeem, Maryam, Muhammad Usman Aslam, and Sobia Shahzad. 2023. "Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing." Global Sociological Review, VIII: 211-220
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MLA : Nadeem, Maryam, Muhammad Usman Aslam, and Sobia Shahzad. "Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing." Global Sociological Review, VIII.I (2023): 211-220 Print.
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OXFORD : Nadeem, Maryam, Aslam, Muhammad Usman, and Shahzad, Sobia (2023), "Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing", Global Sociological Review, VIII (I), 211-220
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TURABIAN : Nadeem, Maryam, Muhammad Usman Aslam, and Sobia Shahzad. "Unravelling the Web of Fake News: Understanding Factors Influencing Fake News Sharing." Global Sociological Review VIII, no. I (2023): 211-220. https://doi.org/10.31703/gsr.2023(VIII-I).20