Personality Recognition from Source Code Based on Lexical, Syntactic and Semantic Features

Automatic personality recognition from source code is a scarcely explored problem. We propose personality recognition with handcrafted features, based on lexical, syntactic and semantic properties of source code. Out of 35 proposed features, 22 features are completely novel. We also show that n-gram features are simple but surprisingly good predictors of personality and present results arising from joint usage of both handcrafted and baseline features. Additionally we compare our results with scores obtained within the Personality Recognition in SOurce COde track during Forum for Information Retrieval Evaluation 2016 and set up state-of-the-art results for conscientiousness and neuroticism traits.