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October 1, 2011482 citations

Our Twitter Profiles, Our Selves: Predicting Personality with Twitter

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DQDaniele QuerciaMKMichał KosińskiDSDavid Stillwell

Key Points

  • This research aims to analyze the relationship between personality traits and Twitter usage patterns among different types of users.
  • Analyzed personality data of 335 Twitter users
  • Identified traits of popular users and influentials
  • Developed a prediction model based on public profile metrics (following, followers, listed counts)
  • Popular users and influentials demonstrated higher extroversion and emotional stability (low neuroticism)
  • Popular users were found to be imaginative (high in openness)
  • Influentials tended to be organized (high in conscientiousness)

Abstract

Psychological personality has been shown to affect a variety of aspects: preferences for interaction styles in the digital world and for music genres, for example. Consequently, the design of personalized user interfaces and music recommender systems might benefit from understanding the relationship between personality and use of social media. Since there has not been a study between personality and use of Twitter at large, we set out to analyze the relationship between personality and different types of Twitter users, including popular users and influentials. For 335 users, we 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 `organized' (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.

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Cite This Study

Quercia et al. (2011) studied this question.

synapsesocial.com/papers/6a0f0aa91c5e2d2319fa447chttps://doi.org/10.1109/passat/socialcom.2011.26
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