Analysis of Social Support Network on the Topic of “Smiling Depression” in Zhihu Online Community

In the era of social media, online communities such as Zhihu have become important platforms for vulnerable groups such as the people who suffer from smiling depression to communicate, learn, and provide or obtain social support from each other. Studying the structural characteristics of online social support network for the topic of “Smiling Depression” can provide an empirical basis for improving the level of social support. This paper takes the topic of “Smiling Depression” in Zhihu platform as the research object, uses Python crawler to collect the answers and comments of top 30 hot questions under this topic, and obtains 238 answers and 4048 comments as valid data. Then, according to the interaction relationship between the answers and commenters, the social support matrix is established. And network density, average degree and other indicators in the social network analysis method are further used to analyze the overall and individual characteristics of the social support network structure. Finally, combining the two indicators of degree centrality and betweenness centrality, core nodes are identified with the identity characteristics analyzed in the social support network.