Social network analytics for churn prediction in telco: Model building, evaluation and network architecture
作者：
Highlights：
• Comparison of Social Networks Analytics methods for predicting churn in telco.
• Ranking of 24 relational learners with respect to predictive performance.
• Collective inferencing does not improve the performance of relational classifiers.
• The best models apply a classifier with network features and relational learner scores.
• Network construction matters for model performance.
摘要
•Comparison of Social Networks Analytics methods for predicting churn in telco.•Ranking of 24 relational learners with respect to predictive performance.•Collective inferencing does not improve the performance of relational classifiers.•The best models apply a classifier with network features and relational learner scores.•Network construction matters for model performance.
论文关键词：Social networks analytics,Churn prediction,Relational learning,Collective inference,Telecommunication industry,Network construction
论文评审过程：Received 6 January 2017, Revised 9 May 2017, Accepted 9 May 2017, Available online 16 May 2017, Version of Record 22 May 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.05.028
