Changing User Behavior in Decisions to Share COVID-19 Misinformation: An Implicit Association Test Study

Authors

Zaid Amin , Nazlena Mohamad Ali , Rahma Santhi Zinaida , Sulaiman Helmi

DOI:

10.29303/jppipa.v10i1.4616

Published:

2024-01-25

Issue:

Vol. 10 No. 1 (2024): January

Keywords:

COVID-19, Implicit association tests, Misinformation sharing, User attention, Visual selective attention system

Research Articles

Downloads

How to Cite

Amin, Z., Ali, N. M. ., Zinaida, R. S. ., & Helmi, S. . (2024). Changing User Behavior in Decisions to Share COVID-19 Misinformation: An Implicit Association Test Study. Jurnal Penelitian Pendidikan IPA, 10(1), 63–71. https://doi.org/10.29303/jppipa.v10i1.4616

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Abstract

Making medical decisions while distracted when receiving COVID-19 misinformation can majorly impact a person's life and even lead to death. Blatantly sharing COVID-19 misinformation is a significant problem of human behavior that triggers a speed-up and acceleration in the propagation and diffusion of misinformation in social media. While the latest research has focused on understanding the psychological dimensions of this phenomenon, few studies have explored the role of selective exposure and technological prevention when a person considers sharing COVID-19 misinformation, primarily through an Implicit Association Test (IAT). Our study identified and intervened in the association of user exposure between misinformation and implicit truth evaluations by using the Implicit Association Test (IAT) with "Misinformation vs. Fact Information or Positive vs. Negative Wordsâ€, 38 from 150 participants were either exposed to misinformation headlines or actual new headline posts on stimulants, in the form of images. We then measured participants' implicit truth evaluations and self-reported perceived accuracies of actual and of misinformation headlines using the Visual Selective Attention System (VSAS). After intervening, participants exposed to fake news headlines had lower implicit truth evaluations and increased perceived accuracy. This implies that exposure to fake news headlines after the intervention with the VSAS system may have directly affected implicit evaluations and changed user behavior in sharing COVID-19 misinformation.

References

Ab Rahman, M. S., Mohamad Ali, N., & Mohd, M. (2017). Comelgetz Prototype in Learning Prayers among Children. Asia-Pacific Journal of Information Technology & Multimedia, 06(01), 115–125. https://doi.org/10.17576/apjitm-2017-0601-09

Amin, Z., Mohamad Ali, N., & Smeaton, A. F. (2021). Attention-Based Design and Selective Exposure Amid COVID-19 Misinformation Sharing. In International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part III 23 (pp. 501–510). Springer. https://doi.org/10.1007/978-3-030-78468-3_34

Bakshy, E., Karrer, B., & Adamic, L. A. (2009). Social influence and the diffusion of user-created content. Proceedings of the ACM Conference on Electronic Commerce, 325–334. https://doi.org/10.1145/1566374.1566421

Barua, Z., Barua, S., Aktar, S., Kabir, N., & Li, M. (2020). Effects of misinformation on COVID-19 individual responses and recommendations for resilience of disastrous consequences of misinformation. Progress in Disaster Science, 8, 100119. https://doi.org/10.1016/j.pdisas.2020.100119

Bonchi, F., Castillo, C., Gionis, A., & Jaimes, A. (2011). Social network analysis and mining for business applications. ACM Transactions on Intelligent Systems and Technology, 2(3), 1–37. https://doi.org/10.1145/1961189.1961194

Carroll, C. E. (2016). Edelman Trust Barometer. The SAGE Encyclopedia of Corporate Reputation, 6, 2022. https://doi.org/10.4135/9781483376493.n106

Chelazzi, L., Perlato, A., Santandrea, E., & Della Libera, C. (2013). Rewards teach visual selective attention. Vision Research, 85, 58–72. https://doi.org/10.1016/j.visres.2012.12.005

Chen, S. S., Chuang, Y. W., & Chen, P. Y. (2012). Behavioral intention formation in knowledge sharing: Examining the roles of KMS quality, KMS self-efficacy, and organizational climate. Knowledge-Based Systems, 31, 106–118. https://doi.org/10.1016/j.knosys.2012.02.001

Chua, A. Y. K., & Banerjee, S. (2017). To share or not to share: The role of epistemic belief in online health rumors. International Journal of Medical Informatics, 108, 36–41. https://doi.org/10.1016/j.ijmedinf.2017.08.010

Erku, D. A., Belachew, S. A., Abrha, S., Sinnollareddy, M., Thomas, J., Steadman, K. J., & Tesfaye, W. H. (2021). When fear and misinformation go viral: Pharmacists’ role in deterring medication misinformation during the “infodemic†surrounding COVID-19. Research in Social and Administrative Pharmacy, 17(1), 1954–1963. https://doi.org/10.1016/j.sapharm.2020.04.032

Fardiah, D., Darmawan, F., & Rinawati, R. (2022). Fact-checking Literacy of Covid-19 Infodemic on Social Media in Indonesia. Komunikator, 14(1), 14–29. https://doi.org/10.18196/jkm.14459

Garson, G. D. (2012). Testing statistical assumptions. Statistical associates publishing Asheboro, NC.

Ghaisani, A. P., Handayani, P. W., & Munajat, Q. (2017). Users’ Motivation in Sharing Information on Social Media. Procedia Computer Science, 124, 530–535. https://doi.org/10.1016/j.procs.2017.12.186

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74(6), 1464–1480. https://doi.org/10.1037/0022-3514.74.6.1464

Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and Using the Implicit Association Test: I. An Improved Scoring Algorithm. Journal of Personality and Social Psychology, 85(2), 197–216. https://doi.org/10.1037/0022-3514.85.2.197

Guo, B., Ding, Y., Yao, L., Liang, Y., & Yu, Z. (2020). The Future of False Information Detection on Social Media: New Perspectives and Trends. ACM Computing Surveys, 53(4), 1–36. https://doi.org/10.1145/3393880

Hodas, N. O., & Lerman, K. (2012). How Visibility and Divided Attention Constrain Social Contagion. 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing, 249–257. https://doi.org/10.1109/SocialCom-PASSAT.2012.129

Isnawijayani, I., Zinaida, R. S., Handianita, G. R. V., Widayatsih, T., Rahayu, S., & Taqwa, D. M. (2022). Communication strategies in the online teaching learning process during pandemic Covid-19. Jurnal Konseling Dan Pendidikan, 10(4). https://doi.org/10.29210/183800

Kaur, M., Verma, R., & Ranjan, S. (2021). Political Leaders’ Communication: A Twitter Sentiment Analysis during Covid-19 Pandemic. Jurnal The Messenger, 13(1), 45. https://doi.org/10.26623/themessenger.v13i1.2585

Khan, M. L., & Idris, I. K. (2019). Recognise misinformation and verify before sharing: a reasoned action and information literacy perspective. Behaviour and Information Technology, 38(12), 1194–1212. https://doi.org/10.1080/0144929X.2019.1578828

Kim, A., & Dennis, A. R. (2019). Says who? The effects of presentation format and source rating on fake news in social media. MIS Quarterly: Management Information Systems, 43(3), 1025–1039. https://doi.org/10.25300/MISQ/2019/15188

Kümpel, A. S., Karnowski, V., & Keyling, T. (2015). News Sharing in Social Media: A Review of Current Research on News Sharing Users, Content, and Networks. Social Media and Society, 1(2). https://doi.org/10.1177/2056305115610141

Laato, S., Islam, A. K. M. N., Farooq, A., & Dhir, A. (2020). Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services, 57, 102224. https://doi.org/10.1016/j.jretconser.2020.102224

Lee, K., & Choo, H. (2013). A critical review of selective attention: An interdisciplinary perspective. Artificial Intelligence Review, 40(1), 27–50. https://doi.org/10.1007/s10462-011-9278-y

Maison, D., Greenwald, A. G., & Bruin, R. (2001). The Implicit Association Test as a measure of implicit consumer attitudes. Blackhorse Publishing. Retrieved from https://depot.ceon.pl/handle/123456789/2576

McAvinue, L. P., Habekost, T., Johnson, K. A., Kyllingsbæk, S., Vangkilde, S., Bundesen, C., & Robertson, I. H. (2012). Sustained attention, attentional selectivity, and attentional capacity across the lifespan. Attention, Perception, and Psychophysics, 74(8), 1570–1582. https://doi.org/10.3758/s13414-012-0352-6

Mosseri, A. (2016). News feed fyi: Addressing hoaxes and fake news. Facebook Newsroom, 15, 12. Retrieved from https://www.scoop.co.nz/stories/WO1612/S00079/news-feed-fyi-addressing-hoaxes-and-fake-news.htm

Munar, A. M., & Jacobsen, J. K. S. (2014). Motivations for sharing tourism experiences through social media. Tourism Management, 43, 46–54. https://doi.org/10.1016/j.tourman.2014.01.012

Muqsith, M. A., Kuswanti, A., Pratomo, R. R., & Muzykant, V. L. (2021). Trump’s Twitter Propaganda During Covid-19. Jurnal The Messenger, 13(3), 223. https://doi.org/10.26623/themessenger.v13i3.3991

Ndinojuo, B.-C. E. (2020). 5G, Religion, and Misconceptions in Communication during Covid-19 in Nigeria. Jurnal The Messenger, 12(2), 97. https://doi.org/10.26623/themessenger.v12i2.2282

Niemantsverdriet, K., Van Essen, H., Pakanen, M., & Eggen, B. (2019). Designing for awareness in interactions with shared systems: The DASS framework. ACM Transactions on Computer-Human Interaction, 26(6), 1–41. https://doi.org/10.1145/3338845

Nosek, B. A. (2007). Implicit–explicit relations. Current Directions in Psychological Science, 16(2), 65–69. https://doi.org/10.1111/j.1467-8721.2007.00477.x

Osatuyi, B. (2013). Information sharing on social media sites. Computers in Human Behavior, 29(6), 2622–2631. https://doi.org/10.1016/j.chb.2013.07.001

Payton, M. E., Greenstone, M. H., & Schenker, N. (2003). Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance? Journal of Insect Science, 3(1). https://doi.org/10.1093/jis/3.1.34

Pennycook, G., Cannon, T. D., & Rand, D. G. (2018). Prior exposure increases perceived accuracy of fake news. Journal of Experimental Psychology: General, 147(12), 1865–1880. https://doi.org/10.1037/xge0000465

Pennycook, G., Epstein, Z., Mosleh, M., Arechar, A. A., Eckles, D., & Rand, D. G. (2021). Shifting attention to accuracy can reduce misinformation online. Nature, 592(7855), 590–595. https://doi.org/10.1038/s41586-021-03344-2

Posner, M. I., Snyder, C. R. R., & Davidson, B. J. (2018). Attention and the detection of signals. Human Perception: Institutional Performance and Reform in Australia, 109(2), 43–57. https://doi.org/10.4324/9781351156288-10

Rapoza, K. (2017). Can “Fake News†Impact the Stock Market? 1. Retrieved from https://www.forbes.com/sites/kenrapoza/2017/02/26/can-fake-news-impact-the-stock-market/?sh=773f869f2fac

Rensink, R. A. (2002). Internal vs external information in visual perception. Proceedings of the 2nd International Symposium on Smart Graphics, 63–70. Retrieved from https://www2.psych.ubc.ca/~rensink/publications/download/sg02-rensink.pdf

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

Vicario, C. M., Salehinejad, M. A., Felmingham, K., Martino, G., & Nitsche, M. A. (2019). A systematic review on the therapeutic effectiveness of non-invasive brain stimulation for the treatment of anxiety disorders. Neuroscience and Biobehavioral Reviews, 96, 219–231. https://doi.org/10.1016/j.neubiorev.2018.12.012

Vicol, D.-O. (2020). Who is most likely to believe and to share misinformation? Africa Check, Chequeado, and Full Fact, February, 9. Retrieved from https://fullfact.org/media/uploads/who-believes-shares-misinformation.pdf

Weng, L., Flammini, A., Vespignani, A., & Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific Reports, 2(1), 335. https://doi.org/10.1038/srep00335

World Health Organization. (2021). Social media & COVID-19: a global study of digital crisis interaction among Gen Z and Millennials. Retrieved from https://www.who.int/news-room/feature-stories/detail/social-media-covid-19-a-global-study-of-digital-crisis-interaction-among-gen-z-and-millennials

Wu, L., Morstatter, F., Carley, K. M., & Liu, H. (2019). Misinformation in Social Media. ACM SIGKDD Explorations Newsletter, 21(2), 80–90. https://doi.org/10.1145/3373464.3373475

Yang, C. T., Little, D. R., & Hsu, C. C. (2014). The influence of cueing on attentional focus in perceptual decision making. Attention, Perception, and Psychophysics, 76(8), 2256–2275. https://doi.org/10.3758/s13414-014-0709-0

Zinaida, R. S., & Havivi, S. L. (2019). Understanding the Communication Strategy of Women’s Rights Protection in the Digital Era through Website. Jurnal The Messenger, 11(2), 244. https://doi.org/10.26623/themessenger.v11i2.1194

Zizlsperger, L., Sauvigny, T., & Haarmeier, T. (2012). Selective attention increases choice certainty in human decision making. PLoS ONE, 7(7), e41136. https://doi.org/10.1371/journal.pone.0041136

Author Biographies

Zaid Amin, Fakultas Sains dan Teknologi, Universitas Bina Darma Universitas Bina Darma

Nazlena Mohamad Ali, Institute of Visual Informatics (IVI) Universiti Kebangsaan Malaysia

Rahma Santhi Zinaida, Fakultas Sosial Humaniora Universitas Bina Darma

Sulaiman Helmi, Pascasarjana Universitas Bina Darma

License

Copyright (c) 2024 Zaid Amin, Nazlena Mohamad Ali, Rahma Santhi Zinaida, Sulaiman Helmi

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).