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The COVID-19 pandemic, which began in the first months of 2020, was almost immediately called “infodemic”: new and often inaccurate information about the virus, its characteristics, and consequences spread at a much higher speed than the virus itself. The term infodemic in a broad sense means the massive dissemination of an excessive amount of information about it during an epidemic (including through media channels), in a narrower sense – panic texts about concealing truthful information, alarm warnings, pseudo-medical advice from non-existent doctors, folk recipes “for protection,” and rumors about the true origin of the disease (bacteriological weapon) (Cinelli et al.). In the situation of the coronavirus epidemic, the most massive in social networks and oral conversations (and with a high degree of trust) are not conspiracy “political” fake news, but texts devoted to folk and pseudo-medical methods of protecting against infection and fighting the disease (Cinelli et al.).
The uncertainty about the virus and the presence of competing hypotheses leads to the blurring of scientific authority and the emergence of various alternative expertises, which can both compete with each other and overlap each other. A situation of “expertise outside the expert community” appears, that is, the production of knowledge outside official expert communities. The “framework” of those is, first of all, the idea of the essence of the virus and the dynamics of its spread, as well as the “knowledge” of how to stop or reduce the spread of the virus, what treatment should be taken, and what place the nation-state and the world-system occupy in this process.
An additional factor that interferes with these processes is the actual participation of artificial intelligence in social interactions as a mediator or active participant (Adly). Self-isolation, “social distancing,” or lockdowns imposed by most governments worldwide could only exacerbate the observed upward trend in online social interactions (Koeze & Popper). In this situation, online culture becomes another critical variable, as it ultimately mediates the deployment of epistemic practices associated with COVID-19 (Lavazza & Farina). Most people today receive information about the new coronavirus from the Internet, but they cannot assess the degree of its reliability or turn to an expert authority due to the crisis of confidence in this latter.
Thus, according to the recommendations of many doctors and WHO representatives, it is necessary to stop or slow down the spread of infodemic so that medical information reaches the population (World Health Organization). However, the use of repressive measures – blocking information sources, the media and social networks, and messengers, the use of criminal punishment for individuals spreading fake news is not considered by the scientific and medical community as adequate measures in this sense. As such, measures are proposed aimed at fostering the ability of the population to analyze incoming information: the emergence of sources devoted to the analysis of fake news, the development of the ability to highlight the main rhetorical strategies used in such texts, and an increase in the general level of media literacy among the population.
Proposed Solution: Filling the Gap
To address the problem of the infodemic, its genesis, and consequences, the study will follow the classification suggested by Benkler and colleagues (Benkler et al.). They proposed the following system of distinctions. First, “Propaganda” and “disinformation”: manipulation and deliberate misleading in order to achieve political goals. Second, “Network propaganda”: the impact of the architecture of the media ecosystem on how easily (or difficult) lies and manipulation spread in this ecosystem. Third, “Bullshit”: communications produced by media that do not care about the truth of their statements and their political effects, being aimed at making a profit. Fourth, “Misinformation”: publishing and disseminating false information without intending to mislead or thereby achieve political goals. Finally, “Disorientation”: a state that a part of propaganda seeks to create, in which the target population group is deprived of the ability to distinguish true information from false, as well as the authority to which it could delegate this task.
The methodology of the study presupposes the analysis of thematic groups in social networks. The primary empirical research questions will concern the socio-demographic characteristics of members of these groups. To address the ecology of media-platforms related to the formation of the COVID-19 infodemic, the study includes a content analysis of discussions and posts with links to third-party resources and a network analysis of links to third-party resources from these groups. The primary research questions will consider what kind of sites with information about COVID-19 are “cited” most often and in which groups, as well as how people react to information on these links. Besides, it is crucial to investigate
the editorial policy of online media on the COVID-19 problem. Here the study will focus on what they do and do not publish, what sources they use, on what grounds they make a decision to publish, and how all this affects clickbait and monetization. This step of investigation presupposes interviews with editors and stakeholders of popular media.
Justification
Over the past 40 years, various researchers have repeatedly suggested that in a metaphorical form, rumors and fakes can “infect” the information carrier just as a virus infects his body, and thereby force a person to change his behavior offline and online (Argyriadis & Argiriadi). However, approaches to the study of the specificity of the emergence and spread of infodemics follow an epidemiological metaphor, which focuses on people as carriers of information.
If the current pandemic is not unprecedented in many other respects, being similar, for example, to the “Spanish” flu of the 1910-1920s, then the media ecology in which it unfolds is indeed new. It is not just about the spread of information and communication technologies (ICT), which led to global synchronization, compression of space-time, and the emergence of a “network society” (Dijk). ICT in general and social media, in particular, are not the neutral medium over which pandemic news travels. Today, these technologies rely on artificial intelligence (AI), big data, and search algorithms that adapt to user preferences and stimulate user reactions to the “content” they deliver. In other words, the novelty of the COVID-19 pandemic lies not only in the widespread of ICT but in the fact that it is deployed in a situation characterized by the participation of AI agents in social interactions as active intermediaries or participants in these interactions.
The essential aspect of the current infodemic is the participation and mediation of “AI agents” in social interactions associated with the production and dissemination of knowledge about the virus, pandemic, their effects, and consequences (Hung et al.). The most important “AI agents” in the deployment of the COVID-19 pandemic were and remain algorithms that analyze data on user activity in social media, reconstruct user preferences based on this data, and determine the priority of displaying certain news on these preferences.
This is not just about using “smart” algorithms, but about making a profit by stimulating user activity, which allows you to more accurately classify data, which, in turn, allows you to make advertising targeted to these users more effective. If, when launching social media platform companies, platform owners and developers actually “sell” their users to third-party application developers to create a network effect, user activity, and “lively” reactions to the posted on the platform (Leetaru). The content turns into key economic assets – in other words, they are capitalized. This circumstance significantly affects the quality and reliability of information circulating in social media: as events of recent years show (Cambridge Analytica, US presidential elections in 2016, Brexit vote, and others), the “networked public sphere” sphere can become a source of full-fledged epistemic crises. Thus, this study focuses on the ecology of information presented on the Internet and considers AI agents as new key actors in the development of a counter-expert agenda.
Works Cited
Adly, Aya Sedky, Afnan Sedky Adly, and Mahmoud Sedky Adly. “Approaches based on artificial intelligence and the internet of intelligent things to prevent the spread of COVID-19: Scoping review.” Journal of Medical Internet Research, vol. 22, no.8, 2020. Web.
Argyriadis, Alexandros, and Agathi Argyriadi. “Socio-Cultural Discrimination and the Role of Media in the Case of the Coronavirus: Anthropological and Psychological Notes through a Case Study.” International Journal of Caring Sciences, vol. 13, no.2, 2020. 1449-1454.
Benkler, Yochai, Robert Faris, and Hal Roberts. Network propaganda: Manipulation, disinformation, and radicalization in American politics. Oxford University Press, 2018.
Cinelli, Matteo, et al. “The covid-19 social media infodemic.” Scientific Reports, vol. 10, no. 16598, 2020. Web.
Hung, Man, et al. “Social network analysis of COVID-19 Sentiments: application of artificial intelligence.” Journal of medical Internet research, vol. 22, no.8, 2020. Web.
Jiang, Julie, et al. “Political polarization drives online conversations about COVID‐19 in the United States.” Human Behavior and Emerging Technologies 2.3 (2020): 200-211.
Koeze, Elle, and Nathaniel Popper. “The Virus Changed the Way We Internet”. The New York Times, 2020, Web.
Leetaru, Kalev. “What Does It Mean For Social Media Platforms To ‘Sell’ Our Data?” Forbes, Forbes Magazine, 2018, Web.
Van Dijk, Jan. The network society. Sage, 2020.
World Health Organization. “Immunizing the Public against Misinformation.” World Health Organization, 2020, Web.
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