You Are What You Eat... Listen to, Watch, and Read

TL;DR

This paper introduces a data-driven approach using LDA on dating profiles to link personality types with media preferences, aiding recommendation systems and addressing the cold start problem.

Contribution

It presents a novel method combining personality profiling with media preference analysis using LDA on real-world dating profile data.

Findings

Certain personality types prefer specific genres, e.g., intuitive thinkers favor sci-fi.

Extraversion correlates with upbeat dance music.

Openness to experience links with jazz, folk, and international cuisine.

Abstract

This article describes a data driven method for deriving the relationship between personality and media preferences. A qunatifiable representation of such a relationship can be leveraged for use in recommendation systems and ameliorate the "cold start" problem. Here, the data is comprised of an original collection of 1,316 Okcupid dating profiles. Of these profiles, 800 are labeled with one of 16 possible Myers-Briggs Type Indicators (MBTI). A personality specific topic model describing a person's favorite books, movies, shows, music, and food was generated using latent Dirichlet allocation (LDA). There were several significant findings, for example, intuitive thinking types preferred sci-fi/fantasy entertainment, extraversion correlated positively with upbeat dance music, and jazz, folk, and international cuisine correlated positively with those characterized by openness to experience. Many other correlations confirmed previous findings describing the relationship among personality, writing style, and personal preferences. (For complete word/personality type assocations see the Appendix).