JMIR Publications

ABSTRACT

Background:

The emergence of social media highlights the decentralized nature of information, which means people can be prone to uncertainty and be affectively polarized. A wealth of research around online affective polarization has focused on quantifying anxiety at an individual level, while neglecting that on a collective basis. To address this gap, the manner in which the anxiety of topic-based communities on social media polarizes warrants further examination.

Objective:

This study aims to gauge the origin and fluctuation in the collective anxiety of topic-based communities on Weibo, and also investigates its correlations with topic characteristics and users’ personal influence.

Methods:

In this paper, researchers proposed a computational model based on neural networks to assess the collective anxiety score of Weibo topic-based communities. The empirical study was based on 200 communities with 403,380 personal accounts and 358,260 messages.

Results:

With demonstrated effectiveness of our computational model (85.00% precision and 87.00% recall), we found correlations between the collective anxiety level and the extent to which a certain topic involves public interest, as well as how community members interpret and elaborate the topics on social network platforms. Furthermore, the ratio of influencers might impact anxiety polarization of topic-based communities by setting tones and leading the trends within their groups. More specifically, how close a certain topic is to public interest and people’s conflicting perceptions are responsible for increases of this collective anxiety, while the number of influencers engaged accounts for the decline of its increment.

Conclusions:

This paper examines the manner in which the anxiety of topic-based communities on Weibo platform polarizes. We found the collective anxiety to 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 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.