A Second Pandemic? Analysis of Fake News about COVID -19 Vaccines in Q atar (2021)

Abstract: While COVID-19 vaccines are finally becoming widely available, a second pandemic that revolves around the circulation of anti-vaxxer “fake news” may hinder efforts to recover from the first one. With this in mind, we performed an extensive analysis of Arabic and English tweets about COVID-19 vaccines, with focus on messages originating from Qatar. We found that Arabic tweets contain a lot of false information and rumors, while English tweets are mostly factual. However, English tweets are much more propagandistic than Arabic ones. In terms of propaganda techniques, about half of the Arabic tweets express doubt, and 1/5 use loaded language, while English tweets are abundant in loaded language, exaggeration, fear, name-calling, doubt, and flag-waving. Finally, in terms of framing, Arabic tweets adopt a health and safety perspective, while in English economic concerns dominate.

## introduction during the covid-19 pandemic, social media have become one of the main communication channels for information dissemination and consumption, and many people rely on them as their primary source of news @xcite , attracted by the broader choice of information sources. unfortunately, over time, social media have also become one of the main channels to spread disinformation. to tackle this issue, a number of (mostly manual) fact-checking initiatives have been launched, and there are over 200 fact-checking organizations currently active worldwide. 1 however, these efforts are insufficient, given the scale of disinformation, which, in the time of covid-19, has grown into the first global infodemic (according to the world health organization). for the tweets in figure 1 , we might want to know whether they are factual, harmful, calling for action, etc. (see section 4.1). it is also important to understand whether the content of the tweet is propagandistic (section 4.2), what propaganda techniques are used, as well as the way the issue is framed (section 4.3). doing this in a timely manner is crucial to help organizations channel their efforts, and to counter the spread of disinformation, which may cause panic, mistrust, and other problems. with this in mind, we performed an extensive analysis of arabic and english tweets about covid-19 and vaccines, with focus on messages originating from qatar. our analysis focuses on (i) covid-19 disinformation, (ii) propaganda and its techniques, and (iii) framing. our contributions can be summarized as follows: ## dataset we collected arabic tweets from february 2020 till march 2021. for the english tweets, we had two separate time periods (before and after covid-19 vaccines became available): (i) from february till august 2020 (644 tweets), and (ii) from november 2020 till january 2021 (1,945 tweets). we used the following keywords to collect the tweets: we collected original tweets (no retweets or replies), we removed the duplicates using the similarity-based approach in @xcite , and we filtered out tweets with less than five words. finally, we kept the most frequently liked and retweeted tweets for annotation. our final corpus consists of 606 arabic and 2,589 english tweets. ## method figure 2 shows the architecture of our system. below, we discuss each analysis step in detail. ## conclusion and future work we have presented our analysis of covid-19 tweets in arabic and english aiming to help in the fight against the global infodemic, which emerged as a result of the covid-19 pandemic. in particular, we collected tweets in different time frames starting from february 2020 till january 2021, and we analyzed them using different aspects of disinformation, propaganda, and framing. we believe that such analysis should help in better understanding the trends over time and across languages. many interesting directions could be pursued in future work. for example, the analysis could be applied to other languages; in fact, we already did a related study for bulgarian @xcite . moreover, while here we focused on tweets, the approach is applicable to other social media platforms such as facebook and whatsapp. (a) arabic: february till august 2020. (b) english: february till august 2020. (c) english: november 2020 till january 2021.