管理科学与工程系学术论坛第八十四讲

主 题：Mining Bilateral Reviews: A Relational Topic Modeling Framework for Transaction Success Prediction in Sharing Economy

主讲人: 陈佳威（清华大学经管学院博士生）

时 间：2019-01-11 08:30

地 点：明德商学楼712室

语 言：英

For sharing economy platforms such as Airbnb, how to improve transaction success rate is a vital issue. We develop an integrated modeling framework that analyzes item descriptions and online user reviews for transaction success prediction. Different from using unilateral reviews in traditional online markets, we incorporate bilateral reviews common in sharing economy to predict results of potential transactions, which has not been addressed in the literature before. A new relational topic model is developed to capture the process of leveraging textual information to predict transaction results. Within the framework of the relational topic model, we embed a topic structure with both shared and private topics to better handle text corpora generated from different sources. This new relational topic model framework facilitates the extraction of the appropriate topic structure from different document collections which helps enhance transaction success prediction performances. Comprehensive experiments conducted on a real-world dataset based on Airbnb demonstrate that our new model significantly outperforms other alternatives.