Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6837324 | Computers in Human Behavior | 2016 | 9 Pages |
Abstract
This study attempts to investigate the online expressive behavior of social media users in China. Specifically, we combine machine learning-based textual analysis with social network analysis to examine the structure and content of the discussion network which formed around the political aspects of food safety issues on China's Twitter-like Weibo. The findings suggest that Weibo-mediated communication space does not serve as an effective forum for deliberative discussion because people of like mind tend to cluster and the factor of emotion predominates. Further statistical analyses of a hand-coded sample show that emotional discussions influence people more than cognitive discussions, with distinct emotions (e.g., anger, fear and sadness) having different effects. A poster's status is also found to matter. We contend that this kind of online civic talk underlines an expressive form of rationality that transcends the dominant bipolar instrumental-communicative dimension for understanding the use of social media in online political discussion.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Yunya Song, Xin-Yu Dai, Jia Wang,