Our Twitter Profiles, Our Selves: Personality and Use of Language

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• Daniele Quercia (University of Cambridge)
• Thursday 06 October 2011, 16:00-17:00
• FW26, Computer Laboratory, William Gates Builiding.

If you have a question about this talk, please contact Eiko Yoneki.

We tested whether Twitter users can be reduced to look-alike nodes (as most of the spreading models would assume) 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 and show that popular and influential users linguistically structure their tweets in specific ways. This suggests 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. Also, for a limited number of 335 users, we are able to gather personality data, analyze it, and find that both popular users and influentials are extroverts and emotionally stable (low in the trait of Neuroticism). Interestingly, we also find that popular users are “imaginative” (high in Openness), while influentials tend to be “organised” (high in Conscientiousness). We then show a way of accurately predicting a user’s personality simply based on three counts publicly available on profiles: following, followers, and listed counts. Knowing these three quantities about an active user, one can predict the user’s five personality traits with a root- mean-squared error below 0.88 on a [1,5] scale. Based on these promising results, we argue that being able to predict user personality goes well beyond our initial goal of informing the design of new personalized applications as it, for example, expands current studies on privacy in social media.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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