Computational model of engagement with stigmatised sentiment: COVID and general vaccine discourse on social media

AbstractThe growth rate of new social media users continues to surpass new Internet users and new unique mobile phone subscribers and this trend remains consistent over the past 5 years (2019 –2023). The most frequently visited types of websites or apps worldwide are chat and messaging, closely followed by social networks and this trend has also remained relatively constant. The dominating role of social media, especially as a source for information seeking, is staggering, particularly during the COVID-19 pandemic. However, the research in Keller et al. (J Mec Internet Res 16:e8, 2014) indicates that not many experts consider social media as a tool for sharing their expertise or for integrating social media into their research efforts. This is a troubling fact, especially consid ering that stigmatised health narrative are fueled in the face of uncertainty and spread very quickly among the lay population. The latter contributes to the spread of misinformation and, consequently, fosters hesitancy about preventive measures such as vaccines. This research presents new evidence on engagement with stigmatised vaccine discourse on Facebook (Meta), Twitter (X), YouTube and Reddit. Engagement with health-related sentiment can be an important indicator of perceptions regarding preventive measures. The current research can draw the attention of public health experts to the conne ction between stigmatised discourse and engagement in health discussions, as well as the potential impact ...
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research