ABSTRACT
Background: Under the uncertainty led by the decentralized information on social media, people seek homogeneity in either opinions or affection to establish group identity to better understand the information. This also means they are easily polarized, not only ideologically but also in their actions. Affective polarization is the emotional tendency for people to show animosity toward opposing partisans while seeking homogeneity from fellow partisans. Much research into online affective polarization has focused on quantifying anxiety at an individual level while neglecting that on a collective basis. Therefore, this paper examined the polarization of collective anxiety in topic-based communities on Weibo. Methods: We aim to interpret correlations between collective anxiety online and topic characteristics, user competence, as well as the proportion of influencers of Weibo topic-based communities. Our neural networks model and statistical analysis were based on 200 communities with 403,380 personal accounts and 1,012,830 messages. Results: Collective anxiety levels are correlated to (1) the extent to which a topic captures public interest, (2) how community members articulate topics on social network platforms, and (3) the ratio of influencers in the community. Specifically, people's conflicting perceptions and articulations of topics might increase collective anxiety, while the extent to which a topic is of the public interest and the number of influencers engaged in a topic account for any decline in its ranking. Furthermore, familiarity with a topic does not help predict collective anxiety levels. There are no significant links between community size or interactivity dynamics and the level of collective anxiety in the topic-based community. Our computational model has 85.00% precision and 87.00% recall. Conclusion: This study found the collective anxiety augment due to topic proximities to public interest and members' lack of declarative knowledge on topics, while to decline with an increasing portion of online influencers. These findings indicate that collective anxiety is induced due to a lack of credibility. Also, the amount of conflicting information shared by different people places them in a state of flux. Therefore, a community with more influencers may be more likely to experience anxiety polarization, bringing forth the issue of layered information and inequality.
ABSTRACT
BACKGROUND: First detected in Wuhan, China in December 2019, the COVID-19 pandemic stretched the medical system in Wuhan and posed a challenge to the state's risk communication efforts. Timely access to quality health care information during outbreaks of infectious diseases can be effective to curtail the spread of disease and feelings of anxiety. Although existing studies have extended our knowledge about online health information-seeking behavior, processes, and motivations, rarely have the findings been applied to an outbreak. Moreover, there is relatively little recent research on how people in China are using the internet for seeking health information during a pandemic. OBJECTIVE: The aim of this study is to explore how people in China are using the internet for seeking health information during a pandemic. Drawing on previous research of online health information seeking, this study asks the following research questions: how was the "#COVID-19 Patient Seeking Help" hashtag being used by patients in Wuhan seeking health information on Weibo at the peak of the outbreak? and what kinds of health information were patients in Wuhan seeking on Weibo at the peak of the outbreak? METHODS: Using entity identification and textual analysis on 10,908 posts on Weibo, we identified 1496 patients with COVID-19 using "#COVID-19 Patient Seeking Help" and explored their online health information-seeking behavior. RESULTS: The curve of the hashtag posting provided a dynamic picture of public attention to the COVID-19 pandemic. Many patients faced difficulties accessing offline health care services. In general, our findings confirmed that the internet is used by the Chinese public as an important source of health information. The lockdown policy was found to cut off the patients' social support network, preventing them from seeking help from family members. The ability to seek information and help online, especially for those with young children or older adult members during the pandemic. A high proportion of female users were seeking health information and help for their parents or for older adults at home. The most searched information included accessing medical treatment, managing self-quarantine, and offline to online support. CONCLUSIONS: Overall, the findings contribute to our understanding of health information-seeking behaviors during an outbreak and highlight the importance of paying attention to the information needs of vulnerable groups and the role social media may play.
