What characterize the rumors circulating on social media in Israel in the first wave of COVID-19?

Hodaya Avikasis 1, Adi Shalem-Rabinovich 1, Yehudit Yehezkeli 1, Azi Lev-on 1 *
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1 Ariel University, Ariel, ISRAEL
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 13, Issue 4, Article No: e202352. https://doi.org/10.30935/ojcmt/13681
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ABSTRACT

The outbreak of COVID-19 has transformed our daily lives, raising concerns about transmission, infection, and recovery rates. This has led to a proliferation of rumors. Online social media platforms have played a significant role in fueling the spread of these rumors. To better understand the character of rumors that circulated on social media during the initial months of the COVID-19 crisis, we collected and analyzed the content of around 100 major rumors, collected in Israel mainly from websites that track of the dissemination of rumors. We found that the majority of rumors focused on health-related issues. In addition: (1) The majority of rumors focused on ways to prevent contracting the virus or how to recover from it, with a significant emphasis on the body and health of individuals. There were significantly fewer rumors that addressed more “distant” issues, such as the origin of the virus. (2) Many rumors cited the name of a researcher or institution, either in Israel or abroad, arguably to enhance the credibility of the rumor. (3) While the number of rumors that aimed to downplay the severity of the pandemic (e.g., claims that government institutions intentionally exaggerated the threat, in order to control the population) was relatively small, it was double the number of rumors that inflated the significance of the pandemic (i.e., that it may be more severe and fatal than it appears).
Keywords: social media, rumors, COVID-19

CITATION

Avikasis, H., Shalem-Rabinovich, A., Yehezkeli, Y., & Lev-on, A. (2023). What characterize the rumors circulating on social media in Israel in the first wave of COVID-19?. Online Journal of Communication and Media Technologies, 13(4), e202352. https://doi.org/10.30935/ojcmt/13681

REFERENCES

  • Abbasi, A., Hossain, L., Hamra, J., & Owen, C. (2010). Social networks perspective of firefighters’ adaptive behavior and coordination among them [Paper presentation]. IEEE/ACM International Conference on Green Computing and Communications & International Conference on Cyber, Physical and Social Computing. https://doi.org/10.1109/GreenCom-CPSCom.2010.57
  • Aghababaeian, H., Hamdanieh, L., & Ostadtaghizadeh, A. (2020). Alcohol intake in an attempt to fight COVID-19: A medical myth in Iran. Alcohol, 88, 29-32. https://doi.org/10.1016/j.alcohol.2020.07.006
  • Allport, G. W., & Postman, L. J. (1945). Section of psychology: The basic psychology of rumor. Transactions of the New York Academy of Sciences, 8(2), 61-81. https://doi.org/10.1111/j.2164-0947.1945.tb00216.x
  • Allport, G. W., & Postman, L. J. (1947). The psychology of rumor. Holt.
  • Anthony, S. (1973). Anxiety and rumor. The Journal of Social Psychology, 89(1), 91-98. https://doi.org/10.1080/00224545.1973.9922572
  • Averbach, L. (2016). It happened that WhatsApp messages reached the bereaved mother before the official announcement. Globes. https://www.globes.co.il/news/article.aspx?did=1001121304
  • Bates, L., & Callison, C. (2008). Effect of company affiliation on credibility in the blogosphere [Paper presentation]. The Association for Education in Journalism and Mass Communication Conference.
  • Bezeq Report. (2020). Bezeq internet report, 2019-2020. https://media.bezeq.co.il/pdf/internetreport_2020.pdf
  • Bordia, P., & DiFonzo, N. (2004). Problem solving in social interactions on the Internet: Rumor as social cognition. Social Psychology Quarterly, 67(1), 33-49. https://doi.org/10.1177/019027250406700105
  • Bordia, P., & DiFonzo, N. (2007). Rumor psychology: Social and organizational approaches. American Psychological Association. https://doi.org/10.1037/11503-000
  • Boyle, E. I., Weng, S., Gollub, J., Jin, H., Botstein, D., Cherry, J. M., & Sherlock, G. (2004). GO:: TermFinder–Open source software for accessing gene ontology information and finding significantly enriched gene ontology terms associated with a list of genes. Bioinformatics, 20(18), 3710-3715. https://doi.org/10.1093/bioinformatics/bth456
  • Bruns, A., Harrington, S., & Hurcombe, E. (2020). ‘Corona? 5G? or both?’: The dynamics of COVID-19/5G conspiracy theories on Facebook. Media International Australia, 177(1), 12-29. https://doi.org/10.1177/1329878X20946113
  • Buckner, H. T. (1965). A theory of rumor transmission. Public Opinion Quarterly, 29(1), 54-70. https://doi.org/10.1086/267297
  • Chary, M. A., Overbeek, D. L., Papadimoulis, A., Sheroff, A., & Burns, M. M. (2020). Geospatial correlation between COVID-19 health misinformation and poisoning with household cleaners in the greater Boston area. Clinical Toxicology, 59(4), 320-325. https://doi.org/10.1080/15563650.2020.1811297
  • Comfort, L. K., Ko, K., & Zagorecki, A. (2004). Coordination in rapidly evolving disaster response systems: The role of information. American Behavioral Scientist, 48(3), 295-313. https://doi.org/10.1177/0002764204268987
  • Crano, W. D. (1970). Effect of sex, response order, and expertise in conformity: A dispositional approach. Sociometry, 33, 239-252. https://doi.org/10.2307/2786155
  • Crisci, R., & Kassinove, H. (1973). Effect of perceived expertise, strength of advice, and environmental setting on parental compliance. Journal of Social Psychology, 89, 245-250. https://doi.org/10.1080/00224545.1973.9922597
  • Depoux, A., Martin, S., Karafillakis, E., Preet, R., Wilder-Smith, A., & Larson, H. (2020). The pandemic of social media panic travels faster than the COVID-19 outbreak. Journal of Travel Medicine, 27(3), 1-2. https://doi.org/10.1093/jtm/taaa031
  • Diviani, N., van Den Putte, B., Giani, S., & van Weert, J. C. (2015). Low health literacy and evaluation of online health information: A systematic review of the literature. Journal of Medical Internet Research, 17(5), 112. https://doi.org/10.2196/jmir.4018
  • Doerr, B., Fouz, M., & Friedrich, T. (2012). Why rumors spread so quickly in social networks. Communications of the ACM, 55(6), 70-75. https://doi.org/10.1145/2184319.2184338
  • Esposito, J. L., & Rosnow, R. L. (1984). Cognitive set and message processing: Implications of prose memory research for rumor theory. Language & Communication, 4, 301-315. https://doi.org/10.1016/0271-5309(84)90014-4
  • Fumento, M. (1990). The myth of heterosexual AIDS. Basic Books.
  • Gangloff, B. (1981). Credibilite de l’emetteur, credibilitd du message, et dissuasion: Experimentation en milieu suburbain [Communicator credibility, message credibility, and dissuasion: Experiments in a suburban setting]. Bulletin de Psychologie [Bulletin de Psychology], 34, 748-753.
  • Garfin, D. R., Silver, R. C., & Holman, E. A. (2020). The novel coronavirus (COVID-2019) outbreak: Amplification of public health consequences by media exposure. Health Psychology, 39, 355-357. https://doi.org/10.1037/hea0000875
  • Garrett, R. K. (2011). Troubling consequences of online political rumoring. Human Communication Research, 37(2), 255-274. https://doi.org/10.1111/j.1468-2958.2010.01401.x
  • Hagar, C. (2013). Crisis informatics: Perspectives of trust–Is social media a mixed blessing? School of Information Student Research Journal, 2(2), 2. https://doi.org/10.31979/2575-2499.020202
  • He, L., Yang, H., Xiong, X., & Lai, K. (2019). Online rumor transmission among younger and older adults. SAGE Open, 9(3), 1-9. https://doi.org/10.1177/2158244019876273
  • Heller, J. (2015). Rumors and realities: Making sense of HIV/AIDS conspiracy narratives and contemporary legends. American Journal of Public Health, 105(1), 43-50. https://doi.org/10.2105/AJPH.2014.302284
  • Hovland, C., Janis, I., & Kelley, H. (1953). Communication and persuasion. Yale University Press.
  • Hu, Y., & Sundar, S. S. (2010). Effects of online health sources on credibility and behavioral intentions. Communication Research, 37, 105-132. https://doi.org/10.1177/0093650209351512
  • Jaeger, M. E., Anthony, S., & Rosnow, R. L. (1980). Who hears what from whom and with what effect: A study of rumor. Personality and Social Psychology Bulletin, 6(3), 473-478. https://doi.org/10.1177/014616728063024
  • Jolley, D., & Douglas, K. M. (2014). The effects of anti-vaccine conspiracy theories on vaccination intentions. PloS ONE, 9(2), 89177. https://doi.org/10.1371/journal.pone.0089177
  • Kahneman, D., & Tversky, A. (1979). On the interpretation of intuitive probability: A reply to Jonathan Cohen. Cognition, 7, 409-411. https://doi.org/10.1016/0010-0277(79)90024-6
  • Kimmel, A. J., & Keefer, R. (1991). Psychological correlates of the transmission and acceptance of rumors about AIDS 1. Journal of Applied Social Psychology, 21(19), 1608-1628. https://doi.org/10.1111/j.1559-1816.1991.tb00490.x
  • Kwon, S., Cha, M., Jung, K., Chen, W., & Wang, Y. (2013). Aspects of rumor spreading on a microblog network [Paper presentation]. The International Conference on Social Informatics. https://doi.org/10.1007/978-3-319-03260-3_26
  • Lee, H., & Oh, H. J. (2017). Normative mechanism of rumor dissemination on Twitter. Cyberpsychology, Behavior, and Social Networking, 20(3), 164-171. https://doi.org/10.1089/cyber.2016.0447
  • Lev-On, A. (2012). Communication, community, crisis: Mapping uses and Gratifications in the contemporary media environment. New Media and Society, 14(1), 98-116. https://doi.org/10.1177/1461444811410401
  • Lev-On, A., & Uziel, V. (2018). Live, visual, social, and mobile: Media ecology in emergencies and ordinary times. Online Information Review, 42(4), 545-558. https://doi.org/10.1108/OIR-04-2016-0117
  • Lin, X., Spence, P. R., & Lachlan, K. A. (2016). Social media and credibility indicators: The effect of influence cues. Computers in Human Behavior, 63, 264-271. https://doi.org/10.1016/j.chb.2016.05.002
  • Liu, F., Burton-jones, A., & Xu, D. (2014). Rumors on social media in disasters: Extending transmission to retransmission. In Proceedings of the Pacific Asia Conference on Information Systems. https://doi.org/10.5465/ambpp.2014.13529abstract
  • Manfredo, M. J., & Bright, A. D. (1991). A model for assessing the effects of communication on recreationists. Journal of Leisure Research, 23, 1-20. https://doi.org/10.1080/00222216.1991.11969840
  • McCroskey, J. C. (1966). Scales for the measurement of ethos. Speech Monographs, 33, 65-72. https://doi.org/10.1080/03637756609375482
  • Merchant, R. M., & Lurie, N. (2020). Social media and emergency preparedness in response to novel coronavirus. JAMA, 323, 2011-2012. https://doi.org/10.1001/jama.2020.4469
  • Mian, A., & Khan, S. (2020). Coronavirus: The spread of misinformation. BMC Medicine, 18(1), 1-2. https://doi.org/10.1186/s12916-020-01556-3
  • Navrátil, V., & Navrátil, L. (2015). Preparedness of health system in Israel for mass emergencies. Casopis Lekaru Ceskych [Lekaru Ceskych Magazine], 154(3), 132-136.
  • Ni, Q., Guo, J., Huang, C., & Wu, W. (2020). Community-based rumor blocking maximization in social networks [Paper presentation]. The International Conference on Algorithmic Applications in Management. https://doi.org/10.1007/978-3-030-57602-8_7
  • Oh, H. J., & Lee, H. (2019). When do people verify and share health rumors on social media? The effects of message importance, health anxiety, and health literacy. Journal of Health Communication, 24(11), 837-847. https://doi.org/10.1080/10810730.2019.1677824
  • Osmond, D. H. (2003): Epidemiology of HIV/AIDS in the United States. http://hivinsite.ucsf.edu
  • Palen, L., & Liu, S. B. (2007). Citizen communications in crisis: Anticipating a future of ICT-supported public participation [Paper presentation]. The SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/1240624.1240736
  • Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In L. Berkowitz (Ed.), Advances in experimental social psychology (pp. 123-203). Academic Press. https://doi.org/10.1016/S0065-2601(08)60214-2
  • Pezzo, M. V., & Beckstead, J. W. (2006). A multilevel analysis of rumor transmission: Effects of anxiety and belief in two field experiments. Basic and Applied Social Psychology, 28(1), 91-100. https://doi.org/10.1207/s15324834basp2801_8
  • Pluviano, S., Watt, C., & Della Sala, S. (2017). Misinformation lingers in memory: Failure of three pro-vaccination strategies. PLoS ONE, 12(7), 1-5. https://doi.org/10.1371/journal.pone.0181640
  • Pornpitakpan, C. (2004). The persuasiveness of source credibility: A critical review of five decades’ evidence. Journal of Applied Social Psychology, 34(2), 243-281. https://doi.org/10.1111/j.1559-1816.2004.tb02547.x
  • Rosnow, R. L. (1974). Communications as cultural science. Journal of Communication, 24(3), 26-38. https://doi.org/10.1111/j.1460-2466.1974.tb00386.x
  • Rosnow, R. L. (1980). Psychology of rumor reconsidered. Psychological Bulletin, 87, 578-591. https://doi.org/10.1037/0033-2909.87.3.578
  • Rosnow, R. L., Esposito, J. L., & Gibney, L. (1988). Factors influencing rumor spreading: Replication and extension. Language & Communication, 2, 29-42. https://doi.org/10.1016/0271-5309(88)90004-3
  • Rosnow, R., & Fine, G. (1976). Rumor and gossip: The social psychology of hearsay. Elsevier.
  • Silverman, C. (2015). Lies, damn lies and viral content: How news websites spread (and debunk) online rumors, unverified claims, and misinformation. http://towcenter.org/research/lies-damn-lies-and-viral-content/
  • Simon, T., Goldberg, A., Leykin, D., & Adini, B. (2016). Kidnapping WhatsApp: Rumors during the search and rescue operation of three kidnapped youth. Computers in Human Behavior, 64, 183-190. https://doi.org/10.1016/j.chb.2016.06.058
  • Spence, P. S., Lachlan, K., Westerman, D., & Spates, S. A. (2013). Where the gates matter less: Ethnicity and perceived source credibility in social media health messages. The Howard Journal of Communication, 24, 1-16. https://doi.org/10.1080/10646175.2013.748593
  • Starbird, K., Palen, L., B. Liu, S., Vieweg, S., Hughes, A., Schram, A., Anderson, K. M., Bagdouri, M., White J., McTaggart, C., & Schenk, C. (2012). Promoting structured data in citizen communications during disaster response: An account of strategies for diffusion of the ‘tweak the tweet’ syntax. In C. Hagar (Ed.), Crisis information management: Communication and technologies (pp. 43-62). Chandos Publishing. https://doi.org/10.1016/B978-1-84334-647-0.50003-5
  • Stephens, K. K., & Malone, P. C. (2009). If the organizations won’t give us information …: The use of multiple new media for crisis technical translation and dialogue. Journal of Public Relations Research, 21(2), 229-239. https://doi.org/10.1080/10627260802557605
  • Stiegler, R., Tilley, S., & Parveen, T. (2011). Finding family and friends in the aftermath of a disaster using federated queries on social networks and websites [Paper presentation]. The 2011 13th IEEE International Symposium on Web Systems Evolution. https://doi.org/10.1109/WSE.2011.6081815
  • Suarez-Lledo, V., & Alvarez-Galvez, J. (2021). Prevalence of health misinformation on social media: Systematic review. Journal of Medical Internet Research, 23(1), e17187. https://doi.org/10.2196/17187
  • Sundar, S. S., & Nass, C. (2001). Conceptualizing sources in online news. Journal of Communication, 51(1), 52-72. https://doi.org/10.1111/j.1460-2466.2001.tb02872.x
  • Sweetser, K. D., & Metzgar, E. (2007). Communicating during crisis: Use of blogs as a relationship management tool. Public Relations Review, 33(3), 340-342. https://doi.org/10.1016/j.pubrev.2007.05.016
  • Swindell, J. S., McGuire, A. L., & Halpern, S. D. (2010). Beneficent persuasion: Techniques and ethical guidelines to improve patients’ decisions. Annals of Family Medicine, 8, 260-264. https://doi.org/10.1370/afm.1118
  • Tasnim, S., Hossain, M. M., & Mazumder, H. (2020). Impact of rumors and misinformation on COVID-19 in social media. Journal of Preventive Medicine and Public Health, 53(3), 171-174. https://doi.org/10.3961/jpmph.20.094
  • Tierney, K., Bevc, C., & Kuligowski, E. (2006). Metaphors matter: Disaster myths, media frames, and their consequences in Hurricane Katrina. The Annals of the American Academy of Political and Social Science, 604(1), 57-81. https://doi.org/10.1177/0002716205285589
  • Turner, P. A. (1993). I heard it through the grapevine: Rumor in African-American culture. University of California Press. https://doi.org/10.1525/9780520915572
  • Van Der Linden, S. (2022). Misinformation: Susceptibility, spread, and interventions to immunize the public. Nature Medicine, 28(3), 460-467. https://doi.org/10.1038/s41591-022-01713-6
  • Von Wagner, C., Semmler, C., Good, A., & Wardle, J. (2009). Health literacy and self-efficacy for participating in colorectal cancer screening: The role of information processing. Patient Education and Counseling, 75(3), 352-357. https://doi.org/10.1016/j.pec.2009.03.015
  • 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
  • Wang, Z., Walther, J. B., Pingree, S., & Hawkins, R. P. (2008). Health information, credibility, homophily, and influence via the Internet: Web sites versus discussion groups. Health Communication, 23, 358-368. https://doi.org/10.1080/10410230802229738
  • Wong, J. (2003). China’s failure. http://mail.com/servlet/story/RTGAM.20030404.wSARSchina0404/BNStory/Front
  • Zhang, E., & Fleming, K. (2005). Examination of characteristics of news media under censorship: A content analysis of selected Chinese newspapers’ SARS coverage. Asian Journal of Communication, 15(3), 319-339. https://doi.org/10.1080/01292980500261639
  • Zook, M., Graham, M., Shelton, T., & Gorman, S. (2010). Volunteered geographic information and crowdsourcing disaster relief: A case study of the Haitian earthquake. World Medical & Health Policy, 2(2), 7-33. https://doi.org/10.2202/1948-4682.1069