Mental health-related conversations on social media and crisis episodes: a time-series regression analysis

We aimed to investigate whether daily fluctuations in mental health-relevant Twitter posts are associated with daily fluctuations in mental health crisis episodes. We conducted a primary and replicated time-series analysis of retrospectively collected data from Twitter and two London mental healthcare providers. Daily numbers of ‘crisis episodes’ were defined as incident inpatient, home treatment team and crisis house referrals between 2010 and 2014. Higher volumes of depression and schizophrenia tweets were associated with higher numbers of same-day crisis episodes for both sites. After adjusting for temporal trends, seven-day lagged analyses showed significant positive associations on day 1, changing to negative associations by day 4 and reverting to positive associations by day 7. There was a 15% increase in crisis episodes on days with above-median schizophrenia-related Twitter posts. A temporal association was thus found between Twitter-wide mental health-related social media content and crisis episodes in mental healthcare replicated across two services. Seven-day associations are consistent with both precipitating and longer-term risk associations. Sizes of effects were large enough to have potential local and national relevance and further research is needed to evaluate how services might better anticipate times of higher risk and identify the most vulnerable groups

Discourse Strategies of Fake News in the Anti-vax Campaign

Anti-vaccine controversial debates have been occurring for more than a century. As the debate has moved onto social media, the issue has further developed. For anti-vaccine campaigners the use of Twitter and Facebook means giving them voice and massively amplifying their message. Yet, precisely because social media advertisements and news works on the basis of an algorithm that brings people to see similar news to those they have read before, anti-vax supporters tend to read and to always believe in the same type of news, be it fake or real. In other words, anti-vax supporters cannot discern real and fake news, as they do not realize that scientific fake news is the result of a decontextualization of the medical sources. By drawing on CDA, corpus linguistics and socio-semiotic multimodality, this paper aims at analyzing fake news discursive dynamics and strategies related to the anti-vax campaign to unveil cognitive, social and institutional constructs of misinformation

Spreading (dis)trust in Fiji? Exploring COVID-19 misinformation on Facebook forums

The COVID-19 pandemic has caused significant challenges for the health system across the globe and fueled the surge of numerous rumours, hoaxes, and misinformation regarding outcomes, prevention and cure of the virus.  The COVID-19 pandemic has also had severe political, economic and societal effects and affected media and communication systems in unprecedented ways. While traditional journalism has tried to adapt to the rapidly evolving situation, alternative news media on the internet have given the events an ideological spin. These voices have been criticised for furthering societal confusion and spreading potentially dangerous ‘fake news’ or conspiracy theories via social media and other online channels. The impact of the disease and the lack of information associated with it have allowed medical misinformation to rapidly surface and propagate on various social media platforms. Previous studies have highlighted a similar trend during recent public health emergencies, mainly the Ebola and Zika outbreaks. Such a phenomenon is alarming on both individual and public health levels to the extent that governments are realising the gravity and attempting to limit its effects. This article offers a unique perspective because it provides data-driven qualitative insights into Fijian Facebook posts related to infectious disease outbreaks. This study aims to understand public views and opinions on Fijian social media during the height of the pandemic in 2020 and to outline potential implications for health information

Systematic Literature Review on the Spread of Health-related Misinformation on Social Media.

Contemporary commentators describe the current period as "an era of fake news" in which misinformation, generated intentionally or unintentionally, spreads rapidly. Although affecting all areas of life, it poses particular problems in the health arena, where it can delay or prevent effective care, in some cases threatening the lives of individuals. While examples of the rapid spread of misinformation date back to the earliest days of scientific medicine, the internet, by allowing instantaneous communication and powerful amplification has brought about a quantum change. In democracies where ideas compete in the marketplace for attention, accurate scientific information, which may be difficult to comprehend and even dull, is easily crowded out by sensationalized news. In order to uncover the current evidence and better understand the mechanism of misinformation spread, we report a systematic review of the nature and potential drivers of health-related misinformation. We searched PubMed, Cochrane, Web of Science, Scopus and Google databases to identify relevant methodological and empirical articles published between 2012 and 2018. A total of 57 articles were included for full-text analysis. Overall, we observe an increasing trend in published articles on health-related misinformation and the role of social media in its propagation. The most extensively studied topics involving misinformation relate to vaccination, Ebola and Zika Virus, although others, such as nutrition, cancer, fluoridation of water and smoking also featured. Studies adopted theoretical frameworks from psychology and network science, while co-citation analysis revealed potential for greater collaboration across fields. Most studies employed content analysis, social network analysis or experiments, drawing on disparate disciplinary paradigms. Future research should examine susceptibility of different sociodemographic groups to misinformation and understand the role of belief systems on the intention to spread misinformation. Further interdisciplinary research is also warranted to identify effective and tailored interventions to counter the spread of health-related misinformation online