In the Mood for Being Influential on Twitter

Researchers have widely studied how information diffuses in Twitter and have often done so by modeling the social-networking site as a communication graph in which tweets spread depending on its nodes' graph properties (e.g., degree, centrality). The resulting models are tractable but make a crucial assumption: that the human being behind an account is a node and that, consequently, human expression in Twitter can be modeled as a set of abstract nodes communicating with each other. We set out to test whether Twitter users can be reduced to look-alike nodes or, instead, whether they show individual differences that impact their popularity and influence. One aspect that may differentiate users is their character and personality. The problem is that personality is difficult to observe and quantify on Twitter. It has been shown, however, that personality is linked to what is unobtrusively observable in tweets: the use of language. We thus carry out a study of tweets - more specifically, we compare five different categories of user (one of which is influencer) and look at their language use. We find that popular and influential users linguistically structure their tweets in specific ways, and that influential users tend to be individuals who express negative sentiment in part of their tweets. These findings suggest that the popularity and influence of a Twitter account cannot be simply traced back to the graph properties of the network within which it is embedded, but also depends on the personality and emotions of the human being behind it.