REDUCING RECOMMENDATION INEQUALITY VIA TWO-SIDED MATCHING: A FIELD EXPERIMENT OF ONLINE DATING

• 成果类型: Article
• 署名作者: Chen, Kuan-Ming; Hsieh, Yu-Wei; Lin, Ming-Jen
• 署名单位: National Taiwan University; Amazon.com
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/iere.12631
• 发表日期: 2023
• 页码: 1201-1221
• 关键词: mate preferences

摘要

Leading dating platforms usually recommend only a small fraction of users based on users' popularity and similarity, leading to recommendation inequality. We use a stylized matching model from economics to modify existing algorithms to reduce inequality. We evaluate the proposed method through a large-scale field experiment on a dating platform. Experiment results suggest that our recommender reduces inequality, improves predictive accuracy, and leads to substantially more matched couples than other competing algorithms.