Social Disclosure Behavior: Investigating Fake News Sharing on Social Media and News Verification Amidst the Covid-19
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Spreading false information about health-related issues on social media platforms has drawn significant attention from all over the world. In addition to this, the reliance on social media for news consumption has made it probable for false news to be disseminated extensively as it is not expensive, easy to use, and quick to send. During the COVID-19 pandemic, social media platforms have seen an increase in the sharing of information, which has also contributed to the propagation of deceptive, false, or fake news. This study intends to analyze news verification behavior, social disclosure behavior, and fake news spreading during the COVID-19 pandemic. The study was encouraged by the serious concerns that the widespread transmission of fake news is linked to public health, trust, and societal well-being. By utilizing a quantitative methodology, the data was gathered by an electronically administrated survey from social media users from different universities in Lahore by using a sample size of 400. The study has found that the general behavior of social media users is to not verify news from other sources, especially during crisis situations when the speed of news sharing increases. This lack of verification contributes to the spread of fake news. It has explored that disclosure behavior leads to the spread of fake news while news verification behavior has a significant negative relationship with fake news sharing.
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Aldwairi, M., & Alwahedi, A. (2018). Detecting fake news in social media networks. Procedia Computer Science, 141, 215–222. https://doi.org/10.1016/j.procs.2018.10.171
Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. The Journal of Economic Perspectives, 31(2), 211–235. http://dx.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, Article e101475. https://doi.org/10.1016/j.tele.2020.101475
Apuke, O. D., Omar, B., & Tunca, E. A. (2023). Effect of fake news awareness as an intervention strategy for motivating news verification behaviour among social media users in Nigeria: Quasi-experimental research. Journal of Asian and African Studies, 58(6), 888–903. http://dx.doi.org/10.1177/00219096221079320
Balakrishnan, V., Ng, K. S., & Rahim, H. A. (2021). To share or not to share–The underlying motives of sharing fake news amidst the COVID-19 pandemic in Malaysia. Technology in Society, 66, Article e101676. https://doi.org/10.1016/j.techsoc.2021.101676
Bazarova, N. N., & Choi, Y. H. (2014). Self-disclosure in social media: Extending the functional approach to disclosure motivations and characteristics on social network sites. Journal of Communication, 64(4), 635–657. http://dx.doi.org/10.1111/jcom.12106
Castioni, P., Andrighetto, G., Gallotti, R., Polizzi, E., & De Domenico, M. (2022). The voice of few, the opinions of many: Evidence of social biases in Twitter COVID-19 fake news sharing. Royal Society Open Science, 9(10), Article e220716. https://doi.org/10.1098/rsos.220716
Chen, J., & Wang, Y. (2021). Social media use for health purposes: systematic review. Journal of Medical Internet Research, 23(5), Article e17917. https://doi.org/10.2196/17917
Cheung, M. S. C., & Lau, R. S. M. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296–325. http://dx.doi.org/10.1177/1094428107300343
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publication.
Derlega, V. J., & Grzelak J. (1979). Appropriateness of self-disclosure. In G. J. Chelune (Ed.), Self-disclosures: Origins, patterns and implications of openness in interpersonal relationships (pp. 151–176). Jossey-Bass.
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method. John Wiley & Sons.
Domenico, G. D., Sit, J., Ishizaka, A., & Nunan, D. (2021). Fake news, social media and marketing: A systematic review. Journal of Business Research, 124, 329–341. http://dx.doi.org/10.1016/j.jbusres.2020.11.037
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192–3198. http://dx.doi.org/10.1016/j .jbusres.2015.12.008
Heir, J. F., Black, W.C. & Babin, J. B. (2013). Multivariate data analysis: A global perspective (7th ed.). Cengage.
Harmon, L. W., Krapels, R. H., & DeCotiis, T. A. (1997). Common method variance in U.S. and Dutch organizational research. Journal of Management, 23(5), 709–743.
Ibrahim, Y., Safieddine, F., & Pourghomi, P. (2023). Attitudes to fake news verification: Youth orientations to ‘right click’authenticate. Journal of Applied Journalism & Media Studies, 12(1), 77–97. https://doi.org/10.1386/ajms_00051_1
Islam, A. N., Laato, S., Talukder, S., & Sutinen, E. (2020). Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive loads perspective. Technological forecasting and social change, 159, Article e120201. https://doi.org/10.1016/j. techfore.2020.120201
Kallberg, J., Burk, R. A., & Thuraisingham, B. (2020). COVID-19: The information warfare paradigm shift. The Cyber Defence Review, 5(3), 161–168. https://doi.org/10.48550/arXiv.2009.01267
Kapoor, A., Guha, S., Das, M. K., Goswami, K. C., & Yadav, R. (2020). Digital healthcare: The only solution for better healthcare during COVID-19 pandemic? Indian Heart Journal, 72(2), 61–64. https://doi.org/10.1016/j.ihj.2020.04.001
Majerczak, P., & Strzelecki, A. (2022). Trust, media credibility, social ties, and the intention to share towards information verification in an age of fake news. Behavioral Sciences, 12(2), Article e51. https://doi.org/10.3390/bs12020051
Mumtaz, A. M., Ting, H., Ramayah, T., Chuah, F., & Cheah, J. H. (2017). Editorial, ‘a review of the methodological misconceptions and guidelines related to the application of structural equation modelling: A Malaysian scenario’. Journal of Applied Structural Equation Modeling, 11(1), 1–13. http://dx.doi.org/10.47263/JASEM.1(1)01
Naeem, S. B., Bhatti, R., & Khan, A. (2021). An exploration of how fake news is taking over social media and putting public health at risk. Health Information and Libraries Journal, 38(2), 143–149. https://doi.org/10.1111/hir.12320
Olan, F., Jayawickrama, U., Arakpogun, E. O., Suklan, J., & Liu, S. (2022). Fake news on social media: the Impact on Society. Information Systems Frontiers, 26, 443–458. https://doi.org/10.1007/s10796-022-10242-z
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
Plotnick, L., Hiltz, S., Grandhi, S., & Dugdale, J. (2019). Real or fake? User behavior and attitudes related to determining the veracity of social media posts. arXiv:1904.03989. https://doi.org/10.48550/arXiv.1904.03989
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & 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
Prier, J. (2017). Commanding the trend: Social media as information warfare. In C. Whyte, A. T. Thrall & B. M. Mazanec (Eds.), Information warfare in the age of cyber conflict (pp. 50–85). Routledge.
Ranzini, G., Newlands, G., & Lutz, C. (2020). Sharenting, peer influence, and privacy concerns: A study on the Instagram-sharing behaviors of parents in the United Kingdom. Social Media+ Society, 6(4), 1–13. https://doi.org/10.1177/2056305120978376
Rowley, J. (2014). Designing and using research questionnaires. Management Research Review, 37(3), 308–330. https://doi.org/10.1108/MRR-02-2013-0027
Sampat, B., & Raj, S. (2022). Fake or real news? Understanding the gratifications and personality traits of individuals sharing fake news on social media platforms. Journal of Information Management, 74(5), 840–876. http://dx.doi.org/10.1108/AJIM-08-2021-0232
Sample, C., Justice, C., & Darraj, E. (2019). A model for evaluating fake news. Cyber Defence Review, 171–192. https://hdl.handle.net/1805/24572
Saunders, M., Lewis, P., & Thornhill, A. (2017). Research methods for business students (8th ed.). Pearson.
Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter, 19(1), 22–36. http://dx.doi.org/10.1145/ 3137597.3137600
Sunstein, C. R. (2001). Echo chambers: Bush V. Gore, impeachment, and beyond. Princeton University Press.
Tabish S. A. (2020). COVID-19 pandemic: Emerging perspectives and future trends. Journal of Public Health Research, 9(1), Article e1786. https://doi.org/10.4081/jphr.2020.1786
Talwar, S., Dhir, A., Singh, D., Virk, G. S., & Salo, J. (2020). Sharing of fake news on social media: Application of the honeycomb framework and the third-person effect hypothesis. Journal of Retailing and Consumer Services, 57, Article e102197. https://doi.org/10.1016/j.jretconser.2020.102197
t'Serstevens, F., Piccillo, G., & Grigoriev, A. (2022). Fake news zealots: Effect of perception of news on online sharing behavior. Frontiers in Psychology, 13, Article e859534. https://doi.org/10.3389/fpsyg.2022.859534
Zarocostas, J. (2020). How to fight an infodemic. The Lancet, 395(10225), Article e676. https://doi.org/10.1016/s0140-6736(20)30461-x
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