[3M5-GS-10] AI application

[3M5-GS-10-05] Causal discovery for satisfaction with matched partners in a recommendation-based online dating service

〇Yoichi Kitahara¹ (1. Livesense Inc.)

Keywords:online dating, matching, causal discovery, LiNGAM, psychology

This paper presents an investigation into the causal relationships of satisfaction with 5-minute video chats with matched partners on "knew", a recommendation-based online dating service. The "knew" utilizes user registration information and past evaluation to recommend suitable partners. Following a 5-minute video chat between matched pairs, data is gathered on various aspects of satisfaction with the partner, such as overall satisfaction, appearance, impression, personality, and conversation, type of appearance, and so on. Based on this evaluation, the next partner to improve overall satisfaction is recommended. Therefore, comprehending the evaluation mechanism for overall satisfaction is significant. However, this is challenging due to the intricate relationships. The aim of this study is to discover causal relationships between satisfaction with a video chat partner. Utilizing a causal discovery method LiNGAM, we examined the causal relationships between satisfaction types of both genders and found that higher satisfaction with external aspects such as appearance and impression caused higher satisfaction with internal aspects such as personality, conversation, and compatibility, and ultimately higher overall satisfaction for both genders.