Home⇛Recoletos Multidisciplinary Research Journal⇛vol. 10 no. 2 (2023)

The Determinants of Fake News Adaptation during Covid-19 Pandemic: A Social Psychology Approach

Choon Ling Kwek | Ke Shin Yeow | Li Zhang | Kay Hooi Keoy | Genaro V. Japos

 

Abstract:

Because of COVID-19, people have felt the social distance and have resorted to the internet for information needs. Hence, fake news has become prevalent as people rely on information explored online. This research aims to examine the social-cultural impacts of fake news adaptation behavior from the social psychological perspective by investigating the relationship between collectivism, social support, sense of belonging, social endorsement, fear of missing out, perceived credibility, issue involvement, and adaptation on fake news among young adults in Malaysia. A quantitative research approach with an online self-administered survey was conducted, and 451 responses were obtained through snowball sampling. In the data analysis, measurement and structural equation modeling were adopted. Findings showed that the relationships among adaptation behaviors on fake news were significantly supported. This research consummates the understanding of the influences of social-cultural (collectivism) on the judgment formation of adaptation among internet users on fake news.



References:

  1. Akbar, Z., Toma, I., Garcia, J. M., & Fensel, D. (2015). Measuring the impact of content adaptation on social media engagement. In A. Mesquita & P. Peres (Eds.), Proceedings of the 2nd European conference on social media: ECSM 2015 (pp.1-10). Academic Conferences and Publishing International Limited. https://books.google.com.ph/books?id=VDU7CgAAQBAJ&printsec=frontcover&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false
  2. Alt, D. (2015). College students’ academic motivation, media engagement and fear of missing out. Computers in Human Behavior, 49, 111-119. https://doi.org/10.1016/j.chb.2015.02.057
  3. Arpaci, I., & Baloğlu, M. (2016). The impact of cultural collectivism on knowledge sharing among information technology majoring undergraduates. Computers in Human Behavior, 56, 65-71. https://doi.org/10.1016/j.chb.2015.11.031
  4. Baltar, F., & Brunet, I. (2012). Social research 2.0: Virtual snowball sampling method using Facebook. Internet Research, 22(1), 57-74. https://doi.org/10.1108/10662241211199960
  5. Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497-529. https://pubmed.ncbi.nlm.nih.gov/7777651/
  6. Behar-Horenstein, L. S., & Feng, X. (2017). Dental student, resident, and faculty attitudes toward treating Medicaid patients. Journal of Dental Education, 81(11), 1291-1300. https://doi.org/10.21815/JDE.017.087
  7. Beyens, I., Frison, E., & Eggermont, S. (2016). I don’t want to miss a thing: Adolescents’ fear of missing out and its relationship to adolescents’ social needs, Facebook use, and Facebook related stress. Computers in Human Behavior, 64, 1-8. https://doi.org/10.1016/j.chb.2016.05.083
  8. Bhawuk, D. P. (2017). Individualism and collectivism. In Y.Y. Kim (Ed.), The international encyclopedia of intercultural communication. John Wiley & Sons, Inc. https://doi.org/10.1002/9781118783665.ieicc0107
  9. Bond, R. M., Settle, J. E., Fariss, C. J., Jones, J. J., & Fowler, J. H. (2017). Social endorsement cues and political participation. Political Communication, 34(2), 261-281. https://doi.org/10.1080/10584609.2016.1226223
  10. Borah, P., & Xiao, X. (2018). The importance of ‘likes’: The interplay of message framing, source, and social endorsement on credibility perceptions of health information on Facebook. Journal of Health Communication, 23(4), 399-411. https://doi.org/10.1080/10810730.2018.1455770
  11. Chua, A. Y. K., & Banerjee, S. (2018). Rumors and rumor corrections on Twitter: Studying message characteristics and opinion leadership. In 2018 4th international conference on information management (ICIM) (pp. 210-214). IEEE. https://doi.org/10.1109/INFOMAN.2018.8392837
  12. Chung, M. (2016). Social endorsement effects on message processing: Cross-cultural analysis. Journal of Communication Arts, 34(3). https://so02.tci-thaijo.org/index.php/jcomm/article/view/86008
  13. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587
  14. Datta, R., Yadav, A. K., Singh, A., Datta, K., & Bansal, A. (2020). The infodemics of COVID-19 amongst healthcare professionals in India. Medical Journal Armed Forces India, 76(3), 276-283. https://doi.org/10.1016/j.mja.2020.05.009
  15. Fornell, C., & Cha, J. (1994). Partial least squares. In R.P. Bagozzi (Ed.), Advanced methods of marketing research (pp52-78). Basil Blackwell. https://books.google.com.ph/books?id=bOxUEAAAQBAJ&printsec=frontcover&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false
  16. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  17. Gardner, A. N. (2019). User's ability to detect fake news in online environments [Master’s thesis, University of Louisville]. ThinkIR The University of Louisville’s Institutional Repository. https://ir.library.louisville.edu/etd/3143/
  18. Gardner, R. G., Harris, T. B., Li, N., Kirkman, B. L., & Mathieu, J. E. (2017). Understanding “it depends” in organizational research: A theory-based taxonomy, review, and future research agenda concerning interactive and quadratic relationships. Organizational Research Methods, 20(4), 610-638. https://doi.org/10.1177/1094428117708856
  19. Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101- 107. https://doi.org/10.2307/2334290
  20. Germani, A., Buratta, L., Delvecchio, E., & Mazzeschi, C. (2020). Emerging adults and COVID-19: The role of individualism-collectivism on perceived risks and psychological maladjustment. International Journal of Environmental Research and Public Health, 17(10), 3497. https://doi.org/10.3390/ijerph17103497
  21. Goodwin, R., & Plaza, S.H. (2000). Perceived and received social support in two cultures: Collectivism and support among British and Spanish students. Journal of Social and Personal Relationships, 17(2), 282-291. https://doi.org/10.1177/0265407500172
  22. Guo, T. C., & Cheng, Z. C. (2016). Sense of belonging based on novel posting: Individuals’ processes of social and psychological integration into virtual groups. Online Information Review, 40(2), 204-217. https://doi.org/10.1108/OIR-06-2015-0198
  23. Hair, J. F. Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.
  24. Hajli, M. N., Sims, J., Featherman, M., & Love, P.E.D. (2015). Credibility of information in online communities. Journal of Strategic Marketing, 23(3), 238-253. https://doi.org/10.1080/0965254X.2014.920904
  25. Hui, E. C. M., Wong, F. K. W., Chung, K. W., & Lau, K. Y. (2014). Housing affordability, preferences and expectations of elderly with government intervention. Habitat International, 43, 11-21. https://doi.org/10.1016/j.habitatint.2014.01.010
  26. Hutcheon, L. (2013). A theory of adaptation (2nd ed.). Routledge. Kastenmüller, A., Greitemeyer, T., Jonas, E., Fischer, P., & Frey, D. (2010). Selective exposure: The impact of collectivism and individualism. The British Journal of Social Psychology, 49(4), 745-763. https://doi.org/10.1348/014466609X478988
  27. Keshavarz, R., & Baharudin, R., (2009). Parenting style in a collectivist culture of Malaysia. European
  28. Journal of Social Sciences, 10(1), 66-73. http://psasir.upm.edu.my/id/eprint/16042/
  29. Kliem, S., Mößle, T., Rehbein, F., Hellmann, D. F., Zenger, M., & Brähler, E. (2015). A brief form of the perceived social support questionnaire (F-SozU) was developed, validated, and standardized. Journal of Clinical Epidemiology, 68(5), 551-562. https://doi.org/10.1016/j.jclinepi.2014.11.003
  30. Kline, R.B. (2010). Principles and practice of structural equation modeling (3rd ed.). Guilford Press. Kumar, S., Huang, B., Cox, R. A. V., & Carley, K. M. (2021). An anatomical comparison of fake-news and trusted-news sharing pattern on Twitter. Computational and Mathematical Organization Theory, 27, 109-133. https://doi.org/10.1007/s10588-019-09305-5
  31. Lobburi, P. (2011). The influence of organizational and social support on turnover intention in collectivist contexts. Journal of Applied Business Research, 28(1), 93-104. https://doi.org/10.19030/jabr.v28i1.6687
  32. Love, M. S. (2007). Security in an insecure world: An examination of individualism‐collectivism and psychological sense of community at work. Career Development International, 12(3), 304-320. https://doi.org/10.1108/13620430710745917
  33. Lui, P. P., & Rollock, D. (2018). Greater than the sum of its parts: Development of a measure of collectivism among Asians. Cultural Diversity and Ethnic Minority Psychology, 24(2), 242-259. https://doi.org/10.1037/cdp0000163
  34. Malaysian Communications and Multimedia Commission. (2018). Internet users survey 2018: Statistical brief number twenty-three. Retrieved June 13, 2020, from https://www.mcmc.gov.my/skmmgovmy/media/General/pdf/Internet-Users-Survey-2018.pdf
  35. Malhotra, N. K. (2019). Marketing research: An applied orientation (7th ed). Pearson Education.
  36. Manalu, S.R., Pradekso, T., & Setyabudi, D. (2018). Understanding the tendency of media users to consume fake news. Jurnal Ilmu Komunikasi, 15(1), 1-16. https://doi.org/10.24002/jik.v15i1.1322
  37. McBeath, M. L. (2015). Sense of belonging, peer support, and social media: Examining the mental health, well-being and school to work transitions of co-operative and non-co-operative education students [Master's thesis, University of Waterloo]. UWSpace. https://uwspace.uwaterloo.ca/bitstream/handle/10012/10096/McBeath_Margaret.pdf;sequence=5
  38. McCroskey,J.C.,&Young,T. J. (1981).Ethosand credibility: The construct and its measurement after three decades. Central States Speech Journal, 32(1), 24-34. https://doi.org/10.1080/10510978109368075
  39. Messing, S., & Westwood, S. J. (2012). 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
  40. Nunnally, J.C. (1978). Psychometric theory (2nd ed.). McGraw-Hill. Podsako, P. M., MacKenzie, S. B., Lee, J. Y., & Podsako, 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
  41. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879-891. https://doi.org/10.3758/brm.40.3.879
  42. Quick, B. L., & Stephenson, M. T. (2007). Authoritative parenting and issue involvement as indicators of ad recall: An empirical investigation of anti-drug ads for parents. Health Communication, 22(1), 25-35. https://doi.org/10.1080/10410230701310273
  43. Quick, B. L., Scott, A. M., & Ledbetter, A. M. (2011). A close examination of trait reactance and issue involvement as moderators of psychological reactance theory. Journal of Health Communication, 16(6), 660-679. https://doi.org/10.1080/10810730.2011.551989
  44. Ramayah, T. J. F. H., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2017). Partial least squares structural equation modeling (PLS-SEM) using smartPLS 3.0: An updated guide and practical guide to statistical analysis. Pearson. https://www.researchgate.net/publication/312460772_Partial_Least_Squares_Structural_Equation_Modeling_PLSSEM_using_SmartPLS_30_An_Updated_and_Practical_Guide_to_Statistical_Analysis
  45. Rampersad, G., & Althiyabi, T. (2020). Fake news: Acceptance by demographics and culture on social media. Journal of Information Technology & Politics, 17(1), 1-11. https://doi.org/10.1080/19331681.2019.1686676
  46. Rapp, D. N., & Salovich, N. A. (2018). Can’t we just disregard fake news? The consequences of exposure to inaccurate information. Behavioral and Brain Sciences, 5(2), 232-239. https://doi.org/10.1177/2372732218785193
  47. Segev, S., Wang, W., & Fernandes, J. (2014). The effects of ad–context congruency on responses to advertising in blogs: Exploring the role of issue involvement. International Journal of Advertising, 33(1), 17-36. https://doi.org/10.2501/IJA-33-1-017-036
  48. Setia, M. S. (2016). Methodology series module 3: Cross-sectional studies. Indian Journal of Dermatology, 61(3), 261-264. https://doi.org/10.4103/0019-5154.182410
  49. Sherman, L. E., Payton, A. A., Hernandez, L. M., Greeneld, P. M., & Dapretto, M. (2016). The power of the like in adolescence: Effects of peer influence on neural and behavioral responses to social media. Psychological Science, 27(7), 1027-1035. https://doi.org/10.1177/0956797616645673
  50. Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322-2347. https://doi.org/10.1108/EJM-02-2019-0189
  51. Soundy, A., Roskell, C., Elder, T., Collett, J., & Dawes, H. (2016). The psychological processes of adaptation and hope in patients with multiple sclerosis: A thematic synthesis. Open Journal of Therapy and Rehabilitation, 4, 22-47. https://doi.org/10.4236/ojtr.2016.41003
  52. Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS Quarterly, 30(3), 679-704. https://doi.org/10.2307/25148745
  53. Stone, M. (1974). Cross-validation and multinomial prediction. Biometrika, 61(3), 509-515. https://doi.org/10.1093/biomet/61.3.509
  54. Talwar, S., Dhir, A., Kaur, P., Zafar, N., & Alrasheedy, M. (2019). Why do people share fake news? Associations between the dark side of social media use and fake news sharing behavior. Journal of Retailing and Consumer Services, 51, 72-82. https://doi.org/10.1016/j.jretconser.2019.05.026
  55. Tandoc, E. C. Jr., Ling, R., Westlund, O., Duy, A., Goh, D., & Lim, Z. W. (2018). Audiences’ acts of authentication in the age of fake news: A conceptual framework. New Media & Society, 20(8), 2745-2763. https://doi.org/10.1177/1461444817731756
  56. United Nations. (2020, April 13). During this coronavirus pandemic, ‘fake news’ is putting lives at risk: UNESCO. https://news.un.org/en/story/2020/04/1061592
  57. Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44, 119-134. https://doi.org/10.1007/s11747-015-0455-4
  58. Wheeler, J. D. III. (2017). How do you like me now? An examination of college students’ use of social media sites [Sociology honors thesis, Bridgewater State University]. Bridgewater State University Virtual Commons. https://vc.bridgew.edu/cgi/viewcontent.cgi?article=1243&context=honors_proj
  59. Wiggins, B. E. (2017). Navigating an immersive narratology: Factors to explain the reception of fake news. International Journal of E-Politics, 8(3), 16-29. https://doi.org/10.4018/IJEP.2017070102
  60. Yoon, H. J., & Tinkham, S. F. (2013). Humorous threat persuasion in advertising: The effects of humor, threat intensity, and issue involvement. Journal of Advertising, 42(1), 30-41. https://doi.org/10.1080/00913367.2012.749082.
  61. Yuan, K. H., Bentler, P. M., & Zhang, W. (2005). The effect of skewness and kurtosis on mean and covariance structure analysis: The univariate case and its multivariate implication. Sociological Methods & Research, 34(2), 240-258. https://doi.org/10.1177/0049124105280200

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