This study employs the news values theory and method in the examination of a large dataset of international news retrieved from Instagram. News values theory itself is subjected to critical examination, highlighting its strengths and weaknesses. Using a mixed method that includes content analysis and topic modeling, the study investigates the major news topics most ‘liked’ by Instagram audiences and compares them with the topics most reported on by news organizations. The findings suggest that Instagram audiences prefer to consume general news, human-interest stories and other stories that are mainly positive in nature, unlike news on politics and other topics on which traditional news organizations tend to focus. Finally, the paper addresses the implications of the above findings.

Background The COVID-19 pandemic has been occurring concurrently with an infodemic of misinformation about the virus. Spreading primarily on social media, there has been a significant academic effort to understand the English side of this infodemic. However, much less attention has been paid to the Arabic side. Objective There is an urgent need to examine the scale of Arabic COVID-19 disinformation. This study empirically examines how Arabic speakers use specific hashtags on Twitter to express antivaccine and antipandemic views to uncover trends in their social media usage. By exploring this topic, we aim to fill a gap in the literature that can help understand conspiracies in Arabic around COVID-19. Methods This study used content analysis to understand how 13 popular Arabic hashtags were used in antivaccine communities. We used Twitter Academic API v2 to search for the hashtags from the beginning of August 1, 2006, until October 10, 2021. After downloading a large data set from Twitter, we identified major categories or topics in the sample data set using emergent coding. Emergent coding was chosen because of its ability to inductively identify the themes that repeatedly emerged from the data set. Then, after revising the coding scheme, we coded the rest of the tweets and examined the results. In the second attempt and with a modified codebook, an acceptable intercoder agreement was reached (Krippendorff α≥.774). Results In total, we found 476,048 tweets, mostly posted in 2021. First, the topic of infringing on civil liberties (n=483, 41.1%) covers ways that governments have allegedly infringed on civil liberties during the pandemic and unfair restrictions that have been imposed on unvaccinated individuals. Users here focus on topics concerning their civil liberties and freedoms, claiming that governments violated such rights following the pandemic. Notably, users denounce government efforts to force them to take any of the COVID-19 vaccines for different reasons. This was followed by vaccine-related conspiracies (n=476, 40.5%), including a Deep State dictating pandemic policies, mistrusting vaccine efficacy, and discussing unproven treatments. Although users tweeted about a range of different conspiracy theories, mistrusting the vaccine’s efficacy, false or exaggerated claims about vaccine risks and vaccine-related diseases, and governments and pharmaceutical companies profiting from vaccines and intentionally risking the general public health appeared the most. Finally, calls for action (n=149, 12.6%) encourage individuals to participate in civil demonstrations. These calls range from protesting to encouraging other users to take action about the vaccine mandate. For each of these categories, we also attempted to trace the logic behind the different categories by exploring different types of conspiracy theories for each category. Conclusions Based on our findings, we were able to identify 3 prominent topics that were prevalent amongst Arabic speakers on Twitter. These categories focused on violations of civil liberties by governments, conspiracy theories about the vaccines, and calls for action. Our findings also highlight the need for more research to better understand the impact of COVID-19 disinformation on the Arab world.

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This study examines the news selection processes followed by fact-checking organizations in the Middle East, specifically Egypt, Jordan, and the United Arab Emirates, and gatekeeping such organizations face while working under authoritarian rule. By reviewing fact-checked news posted on the Facebook pages of six Arabic language organizations: Da Begad, HereszTruth, Fatabyyano, Matsad2sh, MisbarFC, and Saheeh Masr, this study manually analyzes about 5,000 fact-checked news stories to understand the extent of political fact-checking performed on Arab presidents, heads of government, and rulers, along with the most verified news topics. Results show that organizations in the Middle East rarely fact-check Arab rulers or refute their claims, while their news selection process prioritizes human interest topics. The study suggests that Arab fact-checkers resort to self-censorship due to gatekeeping influences that impact the region’s media climate.

UNSTRUCTURED This study empirically examines the way Arabic speakers use specific hashtags on Twitter to express anti-vaccine and anti-pandemic views. By exploring this topic, we aim at filling a gap in literature that can help in understanding Arabic language conspiracies around Covid-19. After downloading a large dataset from Twitter, we content analyzed the most retweeted posts and found that users mostly discuss three specific topics. First, the topic of infringing on civil liberties (43.5%) covers ways that governments have allegedly infringed on civil liberties during the pandemic and unfair restrictions that have been imposed on unvaccinated individuals. This was followed by five varieties of vaccine-related conspiracies (37%), including a Deep State dictating pandemic polices, mistrusting vaccine efficacy, and/or discussing unproven treatments. Finally, calls-for-action (13%) encourage individuals to participate in civil demonstrations. For each of these topics, we also explored the inner logic underpinning some claims, taking examples from prominent conspiracy theories. The implications of the study are discussed in the conclusion and ways to expand the current research are identified.