Predicting Churners of Online Health Communities Based on the User Persona
Wang Ruojia1,Yan Chengxi2,Guo Fengying1,Wang Jimin3()
1School of Management, Beijing University of Chinese Medicine, Beijing 100029, China 2School of Information Resource Management, Renmin University of China, Beijing 100872, China 3Department of Information Management, Peking University, Beijing 100871, China
[Objective] This paper tries to predict user behaviors in online health community based on user persona technology, aiming to identify and keep the potential churners. [Methods] We constructed a multi-dimensional label system for user persona with the help of statistical analysis, social network analysis, natural language processing and LDA topic clustering. Then, we used the decision tree and ensemble learning models to predict the potential churners. [Results] We examined our new model with the Huaxia Traditional Chinese Medicine Forum and its F1 value reached 88.77%. [Limitations] More research is needed to examine our algorithm with other online health communities. [Conclusions] User persona technology could help us predict potential user churns.
王若佳, 严承希, 郭凤英, 王继民. 基于用户画像的在线健康社区用户流失预测研究*[J]. 数据分析与知识发现, 2022, 6(2/3): 80-92.
Wang Ruojia, Yan Chengxi, Guo Fengying, Wang Jimin. Predicting Churners of Online Health Communities Based on the User Persona. Data Analysis and Knowledge Discovery, 2022, 6(2/3): 80-92.
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