COVID -19 in B ulgarian Social Media: Factuality, Harmfulness, Propaganda, and Framing (2021)

Abstract: With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic is currently ranked very high on the list of priorities of the World Health Organization, with dangers ranging from promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic. With this in mind, we studied how COVID-19 is discussed in Bulgarian social media in terms of factuality, harmfulness, propaganda, and framing. We found that most Bulgarian tweets contain verifiable factual claims, are factually true, are of potential public interest, are not harmful, and are too trivial to fact-check; moreover, zooming into harmful tweets, we found that they spread not only rumors but also panic. We further analyzed articles shared in Bulgarian partisan pro/con-COVID-19 Facebook groups and found that propaganda is more prevalent in skeptical articles, which use doubt, flag waving, and slogans to convey their message; in contrast, concerned ones appeal to emotions, fear, and authority; moreover, skeptical articles frame the issue as one of quality of life, policy, legality, economy, and politics, while concerned articles focus on health & safety. We release our manually and automatically analyzed datasets to enable further research.

## introduction the ongoing global covid-19 pandemic has brought an unprecedented situation with a lot of uncertainty: as this was a new disease, very little was known about it. this created an information void, where there was a lot of demand but little supply of reliable new information: a perfect breeding ground for all kinds of rumors and conspiracy theories, whose spread was facilitated by social media, which in turn optimized for user engagement (yet, later, they did put serious efforts in trying to limit the spread of false claims about covid-19). unlike previous events that attracted a lot of disinformation, the emergence of the covid-19 pandemic gave rise to a new powerful blending of medical and political disinformation, which resulted in the first global infodemic. indeed, shortly after having declared the covid-19 outbreak a pandemic, the world health organization had to engage in counter-measures against the growing infodemic, which it ranked among its top priorities in the fight against the covid-19 pandemic. 1 figure 1 shows some tweets that demonstrate how covid-19 is discussed in bulgarian social media. we can see that the problem goes beyond factuality: while some tweets spread rumors (figure 1a ), other discuss cure (figure 1b ). indeed, the infodemic quickly extended to promoting bad cure, instilling panic, xenophobia, racism, and distrust in authorities, among others. @xcite figure 1 : bulgarian tweets with english translation. thus, it is important to analyze social media posts in terms of factuality, harmfulness, checkworthiness, etc. it is also useful to understand whether the post is propagandistic, what propaganda techniques are used, and how the issue is framed. while there have been studies focusing on (some of) these issues for high-resource languages such as english and arabic @xcite @xcite @xcite , there has been less work for low-resource languages such as bulgarian @xcite @xcite . here, we aim to bridge this gap by analyzing tweets and facebook posts about covid-19 in bulgarian, with focus on factuality, harmfulness, propaganda, and framing. our contributions can be summarized as follows: the rest of the paper is organized as follows: section 2 offers a brief overview of previous work. section 3 describes the dataset. section 4 discusses our methodology. section 5 discusses the findings. finally, section 7 concludes and points to possible directions for future work. ## method figure 2 shows our analysis pipeline. below, we discuss each element of the pipeline in more detail. ## results and discussion below, we present the results of our analysis. ## limitations manual annotations our manual annotation for disinformation in tweets shows moderate to substantial agreement across the questions. we believe that this is reasonable given the complexity of the task. ## conclusion and future work we presented our analysis of covid-19 in bulgarian social media with focus on tweets and on news articles posted in facebook groups, which we collected in different time frames starting from january till november 2020. then, we manually and automatically analyzed them using different aspects of disinformation, propaganda, and framing. we believe that the kind of analysis we perform here would help in better understanding various trends in social media about covid-19. see also a related study about covid-19 and vaccines in qatar @xcite . there are a number of interesting research directions that could be pursued using the approaches we used in this study. while we only focused on twitter and facebook, similar analysis can be done on other platforms e.g., whatsapp, gab, reddit.