WORKSHOP (INTERNATIONAL) Estimation of user-specific personality traits on the Web

Satoki Hamanaka (Keio University), Wataru Sasaki (Keio University), Satoko Miyahara, Kota Tsubouchi, Jin Nakazawa (Keio University), Tadashi Okoshi (Keio University)

The Twenty-fourth International Workshop on Mobile Computing Systems and Applications (ACM HotMobile 2023)

February 22, 2023

We focus on user’s personality traits and propose a method to estimate user’s personality traits from footprint logs collected from news platform services and search queries, with the aim of constructing a news recommendation system using the personality traits. We constructed supervised machine learning models for 8871 users, using the features calculated from news browsing logs as explanatory variables and personality traits (Big Five) collected via a questionnaire using crowdsourcing as objective variables. Five estimators were constructed for each Big Five traits, and the results of comparative evaluation using multiple algorithms showed that the accuracy of AUC 0.634 was obtained for the agreeableness trait.

Paper : Estimation of user-specific personality traits on the Web (external link)