Long Chains or Stable Communities? The Role of Emotional Stability in Twitter Conversations

In this paper, we address the issue of how emotional stability affects social relationships in Twitter. In particular we focus our study on users’ communicative interactions, identified by the symbol “@”. We collected a corpus of about 200000 Twitter posts and we annotated it with our personality recognition system. This system exploits linguistic features, such as punctuation and emoticons, and statistical features, such as followers count and retweeted posts. We tested the system on a dataset annotated with personality models produced by human subjects and against a software for the analysis of Twitter data. Social Network Analysis shows that, while secure users have more mutual connections, neurotic users post more than secure ones and have the tendency to build longer chains of interacting users. Clustering coefficient analysis reveals that, while secure users tend to build stronger networks, neurotic users have difficulty in belonging to a stable community, hence they seek for new contacts in online social networks.