Global Misinformation Spillovers in the Vaccination Debate Before and During the COVID-19 Pandemic: Multilingual Twitter Study.

BACKGROUND: Antivaccination views pervade online social media, fueling distrust in scientific expertise and increasing the number of vaccine-hesitant individuals. Although previous studies focused on specific countries, the COVID-19 pandemic has brought the vaccination discourse worldwide, underpinning the need to tackle low-credible information flows on a global scale to design effective countermeasures. OBJECTIVE: This study aimed to quantify cross-border misinformation flows among users exposed to antivaccination (no-vax) content and the effects of content moderation on vaccine-related misinformation. METHODS: We collected 316 million vaccine-related Twitter (Twitter, Inc) messages in 18 languages from October 2019 to March 2021. We geolocated users in 28 different countries and reconstructed a retweet network and cosharing network for each country. We identified communities of users exposed to no-vax content by detecting communities in the retweet network via hierarchical clustering and manual annotation. We collected a list of low-credibility domains and quantified the interactions and misinformation flows among no-vax communities of different countries. RESULTS: The findings showed that during the pandemic, no-vax communities became more central in the country-specific debates and their cross-border connections strengthened, revealing a global Twitter antivaccination network. US users are central in this network, whereas Russian users also became net exporters of misinformation during vaccination rollout. Interestingly, we found that Twitter's content moderation efforts, in particular the suspension of users following the January 6 US Capitol attack, had a worldwide impact in reducing the spread of misinformation about vaccines. CONCLUSIONS: These findings may help public health institutions and social media platforms mitigate the spread of health-related, low-credibility information by revealing vulnerable web-based communities.

Behavior Change Around an Online Health Awareness Campaign: A Causal Impact Study.

National Eating Disorders Association conducts a NEDAwareness week every year, during which it publishes content on social media and news aimed to raise awareness of eating disorders. Measuring the impact of these actions is vital for maximizing the effectiveness of such interventions. This study is an effort to empirically measure the change in behavior of users who engage with NEDAwareness content, and compare the detected changes between campaigns in two different years. We analyze a total of 35,895 tweets generated during two campaigns of NEDAwareness campaigns in 2019 and 2020. In order to assess the reach of each campaign, we consider the users participating in the campaigns and their number of followers, as well as retweeting engagement. We use the Linguistic Inquiry and Word Count (LIWC) text modeling and causal impact analysis in order to gauge the change in self-expression of users who have interacted with the NEDAwareness content, compared to a baseline group of users. We further enrich our understanding of the users by extracting gender information from their display names. We find that, despite large media corporations (such as MTV and Teen Vogue) participating in the campaign, it is governmental and nonprofit accounts who are among the accounts that attract the most retweets. Whereas the most influential accounts were well-connected in 2019, the 2020 campaign saw little retweeting between such accounts, negatively impacting the reach of the material. Both campaigns engaged women at around 40% and men 17%, supporting previous research showing women to be more likely to share their experiences with eating disorders. Further, women were more likely to mention other health topics within the 15 days of the intervention, including pregnancy and abortion, as well as depression and anxiety, and to discuss the developing COVID pandemic in 2020. Despite the positive message of the campaign, we find that the users who have engaged with this content were more likely to mention the linguistic categories concerning anxiety and risk. Thus, we illustrate the complex, gender-specific effects of NEDAwareness online health intervention campaign on the continued self-expression of its audience and provide actionable insights for potential improvement of such public health efforts.

All the lonely people: Effects of social isolation on self-disclosure of loneliness on Twitter

This study explores the effect of unprecedented mass isolation during COVID-19 lockdowns through the lens of self-disclosure of loneliness on Twitter. Using a dataset of 30 million public tweets, we use machine learning to identify tweets that contain self-disclosure of loneliness. We find that thousands more people turned to Twitter to express their loneliness during the lockdowns;however, this effect normalized within a month, demonstrating the ?ordinization? effect on a collective level. Furthermore, lockdown brought a marked shift in the weekly timings of posting and a change in the accompanying emotions, which were more positive and other-focused. Finally, based on a qualitative analysis, we propose an updated typology of loneliness that captures the possibilities offered by the affordances of social media. Our findings illustrate the profound effect lockdowns had on the societal psychological state and emphasize the importance of mental health resources during extreme and isolating events.