Pisco: A Computational Approach to Predict Personality Types from Java Source Code

We developed an approach to automatically predict the personality traits of Java developers based on their source code for the PR-SOCO challenge 2016. The challenge provides a data set consisting of source code with their associated developers’ personality traits (neuroticism, extraversion, openness, agreeableness, and conscientiousness). Our approach adapts features from the authorship identification domain and utilizes features that were specifically engineered for the PR-SOCO challenge. We experiment with two learning methods: linear regression and k-nearest neighbors regressor. The results are reported in terms of the Pearson product-moment correlation and root mean square error. CCS Concepts •Computing methodologies Ñ Artificial intelligence; Natural language processing;