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Psychology research suggests that certain personality traits correlate with linguistic behavior. This correlation can be effectively modeled with statistical natural language processing techniques. Prediction accuracy generally improves with larger data samples, which also allows for more lexical features. Most existing work on personality prediction, however, focuses on small samples and closed-vocabulary investigations. Both factors limit the generality and statistical power of the results. In this paper, we explore the use of social media as a resource for large-scale, open- vocabulary personality detection. We analyze which features are predictive of which personality traits, and present a novel corpus of 1.2M English tweets annotated with Myers-Briggs personality type and gender. Our experiments show that social media data can provide sufficient linguistic evidence to reliably predict two of four personality dimensions.

Personality Traits on Twitter—or—How to Get 1,500 Personality Tests in a Week