Skip to content
BY 4.0 license Open Access Published by De Gruyter Open Access May 22, 2022

Credibility in the time of COVID-19: Cues that audiences look for when assessing information on social media and building confidence in identifying ‘fake news’ about the virus

  • Amber Hinsley EMAIL logo , Ilwoo Ju , Taehwan Park and Jennifer Ohs
From the journal Open Information Science

Abstract

Navigating the COVID-19 pandemic has included parsing an overwhelming amount of information—much of it online. Many Americans have seen information on social media that they find confusing (Mitchell, Oliphant & Shearer, 2020) and recent research has found that social media use may contribute to greater likelihoods of believing misinformation about the virus and sharing ‘fake news’ about it (Su, 2021; Pennycook et al., 2020). Using a survey of U.S. adults, this research determined which social media platforms Americans rely on most when they search for information about COVID-19: Facebook, YouTube and Twitter. The present study also identified the credibility cues that people look to as they are trying to ascertain the veracity of COVID-19 information they come across on social media and that are predictors of helping them feel more confident in their own ability to identify credible information. Those significant cues—believability, authenticity, trustworthiness, reliability and objectivity—confirm previous research by Appelman and Sundar (2016) and Tandoc et al. (2018b). Educators, public health officials, and journalists are among the professionals who can use these findings to create more effective messages designed to assist people in making better health decisions.

References

Alba, D. (2022, Jan. 2). Twitter permanently suspends Majorie Taylor Greene’s account. New York Times. https://www.nytimes.com/2022/01/02/technology/marjorie-taylor-greene-twitter.htmlSearch in Google Scholar

Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: does it matter? Journal of Health and Social Behavior, 36, 1-10.10.2307/2137284Search in Google Scholar

Anderson, M. & Vogels, E.A. (2020, March 31). Americans turn to technology during COVID-19 outbreak, say an outage would be a problem. Pew Research Center. https://www.pewresearch.org/fact-tank/2020/03/31/americans-turn-to-technology-during-covid-19-outbreak-say-an-outage-would-be-a-problem/Search in Google Scholar

Appelman, A., & Sundar, S. S. (2016). Measuring message credibility: Construction and validation of an exclusive scale. Journalism and Mass Communication Quarterly, 93(1), 59-79.10.1177/1077699015606057Search in Google Scholar

Basol, M., Roozenbeek, J., & van der Linden, S. (2020). Good news about bad news: Gamified inoculation boosts confidence and cognitive immunity against fake news. Journal of Cognition, 3(1), 2.10.5334/joc.91Search in Google Scholar

Baum, M.A., Ognyanova, K., Chwe, H., Quintana, A., Perlis, R.H., Lazer, D., Druckman, J., Santillana, M., Lin, J., Della Volpe, J., Simonson, M., and Green, J. (2020, September). The state of the nation: A 50-state COVID -19 survey report #14: Misinformation and vaccine acceptance. The COVID-19 Consortium for Understanding the Public’s Policy Preferences Across States. https://osf.io/w974j/10.31219/osf.io/w974jSearch in Google Scholar

Brummette, J., DiStaso, M., Vafeiadis, M., & Messner, M. (2018). Read all about it: The politicization of “fake news” on Twitter. Journalism & Mass Communication Quarterly, 95(2), 497-517.10.1177/1077699018769906Search in Google Scholar

Chaxel, A.S. (2016). Why, when and how personal control impacts information processing: A framework. Journal of Consumer Research, 43(1), 179-197.10.1093/jcr/ucw013Search in Google Scholar

Chung, C., Nam, Y., & Stefanone, M. (2012). Exploring online news credibility: The relative influence of traditional and technological factors. Journal of Computer-Mediated Communication, 17, 171-186.10.1111/j.1083-6101.2011.01565.xSearch in Google Scholar

Fletcher, R. & Nielsen, R. K. (2018). People Don’t Trust News Media – and This is Key to theSearch in Google Scholar

Global Misinformation Debate. In First Draft News, Annenberg School of Communication and Knight Foundation (Eds). Understanding and Addressing the Disinformation Ecosystem (pp. 13-17). Retrieved from https://firstdraftnews.org/wp-content/uploads/2018/03/The-Disinformation-Ecosystem-20180207-v2.pdfSearch in Google Scholar

Graefe, A., Haim, M., Haarmann, B., & Brosius, H.-B. (2018). Readers’ perception of computer-generated news: Credibility, expertise, and readability. Journalism, 19(5), 595–610.10.1177/1464884916641269Search in Google Scholar

Go, E., Jung, E. H., & Wu, M. (2014). The effects of source cues on online news perception. Computers in Human Behavior 38, 358-367.10.1016/j.chb.2014.05.044Search in Google Scholar

Jahng, M. R. & Littau, J. (2016). Interacting is believing: Interactivity, social cue, and perceptions of journalistic credibility on Twitter. Journalism & Mass Communication Quarterly 93(1), 38-58.10.1177/1077699015606680Search in Google Scholar

Jun, Y., Meng, R. & Johar, G. V. (2017). Perceived social presence reduces fact-checking. Proceedings of the National Academy of Sciences of the United States of America, 114(23), 5976-5981.10.1073/pnas.1700175114Search in Google Scholar

Jurkowitz, M. & Mitchell, A. (2020, March 25). Americans who primarily get news through social media are least likely to follow COVID-19 coverage, most likely to report seeing made-up news. Pew research Center. https://www.journalism.org/2020/03/25/americans-who-primarily-get-news-through-social-media-are-least-likely-to-follow-covid-19-coverage-most-likely-to-report-seeing-made-up-news/Search in Google Scholar

Kang, M. (2010). Measuring Social Media Credibility: A Study on a Measure of Blog Credibility. Institute for Public Relations. https://www.instituteforpr.org//wp-content/uploads/BlogCredibility101210.pdfSearch in Google Scholar

Kaye, B. K., & Johnson, T. J. (2016). Across the great divide: How partisanship and perceptions of media bias influence changes in time spent with media. Jour nal of Broadcasting & Electronic Media, 60(4), 604–623.10.1080/08838151.2016.1234477Search in Google Scholar

Loibl, C., Cho, S.H., Diekmann, F. & Batte, M.T. (2009). Consumer self-confidence in searching for information. Journal of Consumer Affairs, 43(1), 26-55.10.1111/j.1745-6606.2008.01126.xSearch in Google Scholar

Matz, D.C. & Hinsz, V.B. (2000) Social comparison in the setting of goals for own and others’ performance. Journal of Business & Psychology, 14(4), 563-572.10.1023/A:1022934129094Search in Google Scholar

Meriam Library. (2010, Sept. 17). Evaluating information—applying the CRAAP test. California State University, Chico. https://library.csuchico.edu/sites/default/files/craap-test.pdfSearch in Google Scholar

Metzger, M. J., Flanagin, A. J., Eyal, K., & Lemus, D.R. (2003). Credibility for the 21st Century: Integrating perspectives on source, message and media credibility in the contemporary media environment. Annals of the International Communication Association, 27(1), 293-335.10.1080/23808985.2003.11679029Search in Google Scholar

Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60, 413-439.10.1111/j.1460-2466.2010.01488.xSearch in Google Scholar

Mitchell, A., Oliphant, J. B., and Shearer, E. (2020, April 20). About seven-in-ten U.S. adults say they need to take breaks from COVID-19 news. Pew Research Center. https://www.journalism.org/2020/04/29/about-seven-in-ten-u-s-adults-say-they-need-to-take-breaks-from-covid-19-news/Search in Google Scholar

Mourão, R. R., & Robertson, C. T. (2019). Fake news as discursive integration: An analysis of sites that publish false, misleading, hyperpartisan and sensational information. Journalism Studies, 20(14), 2077–2095.10.1080/1461670X.2019.1566871Search in Google Scholar

Nielsen, R.K. & Graves, L. (2017, October). “News you don’t believe:” Audience perspectives on fake news. Reuters Institute. https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2017-10/Nielsen&Gravesfactsheet1710v3FINALdownload.pdfSearch in Google Scholar

Nieva, R. (2021, Jan. 26). YouTube says it’s removed 500,000 COVID-19 misinformation videos. CNet. https://www.cnet.com/news/youtube-says-its-removed-500000-covid-19-misinformation-videos/Search in Google Scholar

Paisana, M., Pinto-Martinho, A., & Cardoso, G. (2020). Trust and fake news: Exploratory analysis of the impact of news literacy on the relations with news content in Portugal. Communication & Society 33(2), 105-117.10.15581/003.33.2.105-117Search in Google Scholar

Pennycook, G., McPhetres, J., Zhang, Y., Lu, J.G., and Rand, D.G. (2020). Fighting COVID-19 misinformation on social media: Experimental evidence for a scalable accuracy-nudge intervention. Psychological Science, 31(7), 770–780.10.1177/0956797620939054Search in Google Scholar

Rosen, G. (2020, April 16). An Update on Our Work to Keep People Informed and Limit Misinformation About COVID-19. Facebook. https://about.fb.com/news/2020/04/covid-19-misinfo-update/Search in Google Scholar

Rosenberg, H., Syed, S. & Rezaie, S. (2020). The Twitter pandemic: The critical role of Twitter in the dissemination of medical information and misinformation during the COVID-19 pandemic. Canadian Journal of Emergency Medicine 22(4), 418-421.10.1017/cem.2020.361Search in Google Scholar

Roth, Y. & Pickles, N. (2020, May 11). Updating our approach to misleading information. Twitter. https://blog.twitter.com/enus/topics/product/2020/updating-our-approach-to-misleading-information.htmlSearch in Google Scholar

Schwarzenegger, C. (2020). Personal epistemologies of the media: Selective criticality, pragmatic trust, and competence–confidence in navigating media repertoires in the digital age. New Media & Society, 22(2), 361-377.10.1177/1461444819856919Search in Google Scholar

Sharma, K., Qian, F., Jiang, H., Ruchansky, N., Zhang, M., Liu, Y. (2019). Combating fake news: A survey on identification and mitigation techniques. ACM Transactions on Intelligent Systems and Technology 10(3), 1-42.10.1145/3305260Search in Google Scholar

Shearer, E. & Mitchell, A. (2021, January 12). News use across social media platforms in 2020. Pew Research Center. https://www.journalism.org/wp-content/uploads/sites/8/2021/01/PJ2021.01.12News-and-Social-MediaFINAL.pdfSearch in Google Scholar

Su, Y. (2021). It doesn’t take a village to fall for misinformation: Social media use, discussion heterogeneity preference, worry of the virus, faith in scientists, and COVID-19-related misinformation beliefs. Telematics and Informatics, 58, forthcoming.10.1016/j.tele.2020.101547Search in Google Scholar

Sundar, S. S., Knobloch-Westerwick, S., & Hastall, M. (2007). News cues: Information scent and cognitive heuristics. Journal of the American Society of Information Science and Technology, 58 (3), 366–378.10.1002/asi.20511Search in Google Scholar

Tandoc, E. C., Lim, Z. W., & Ling, R. (2018a). Defining “fake news:” A typology of scholarly definitions. Digital Journalism, 6(2), 137-153.10.1080/21670811.2017.1360143Search in Google Scholar

Tandoc, E.C., Ling, R., Westlund, O., Duffy, A., Goh, D., & Lim, Z. W. (2018b). Audiences’ acts of authentication in the age of fake news: A conceptual framework. New Media & Society, 20(8), 2745–2763.10.1177/1461444817731756Search in Google Scholar

Tankovska, H. (2021, Jan. 28) Share of U.S. population who use social media 2008-2019. Statista. https://www.statista.com/statistics/273476/percentage-of-us-population-with-a-social-network-profile/Search in Google Scholar

Tirso, R. & Geraci, L. (2020). Taking another perspective on overconfidence in cognitive ability: A comparison of self and other metacognitive judgments. Journal of Memory and Language, Advanced online publication.10.1016/j.jml.2020.104132Search in Google Scholar

Tong, C., Gill, H., Li, J., Valenzuela, S., & Rojas, H. (2020). ‘Fake News Is Anything They Say!’ Conceptualization and weaponization of fake news among the American public. Mass Communication and Society, 23(5), 755–778.10.1080/15205436.2020.1789661Search in Google Scholar

Van Duyn, E., & Collier, J. (2019). Priming and fake news: The effects of elite discourse on evaluations of news media. Mass Communication and Society, 22(1), 29–48.10.1080/15205436.2018.1511807Search in Google Scholar

Wan, E.W. & Rucker, D.D. (2013). Confidence and construal framing: When confidence increases versus decreases information processing. Journal of Consumer Research, 39(5), 977-992.10.1086/666467Search in Google Scholar

Westerwick, A., Johnson, B. K., & Knobloch-Westerwick, S. (2017) Confirmation biases in selective exposure to political online information: Source bias v. content bias. Communication Monographs, 84(3), 343-364.10.1080/03637751.2016.1272761Search in Google Scholar

Winter, S., Metzger, M., & Flanagin, A. (2017). Selective use of news cues: A multiple-motive perspective on information selection in social media environments. Journal of Communication, 66(4), 669-693.10.1111/jcom.12241Search in Google Scholar

World Health Organization. (2022, January 7). WHO coronavirus disease (COVID-19) dashboard. https://covid19.who.int/Search in Google Scholar

Yaqub, W., Kakhidze, O., Brockman, M.L., Memon, N., & Patil, S. (2020). Effects of Credibility Indicators on Social Media News Sharing Intent. CHI ‘20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. p. 1-14 April 2020 Honolulu, HI https://dl.acm.org/doi/abs/10.1145/3313831.337621310.1145/3313831.3376213Search in Google Scholar

YouTube. (2021, Feb. 18). Coronavirus 2019 (COVID-19) updates. https://support.google.com/youtube/answer/9777243?hl=en#Search in Google Scholar

Young, L. E., Sidnam-Mauch, E., Twyman, M., Wang, L., Xu, J. J., Sargent, M., Valente, T. W., Ferrara, E., Fulk, J., & Monge, P. (2021). Disrupting the COVID-19 misinfodemic with network interventions: Network solutions for network problems. American Journal of Public Health, 111(3), 514–519.10.2105/AJPH.2020.306063Search in Google Scholar

Received: 2021-02-26
Accepted: 2022-04-05
Published Online: 2022-05-22

© 2022 Amber Hinsley et al., published by De Gruyter

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

Downloaded on 7.12.2023 from https://www.degruyter.com/document/doi/10.1515/opis-2022-0132/html
Scroll to top button