Joint Effects of Context and User History for Predicting Online Conversation Re-entries.

摘要: As the online world continues its exponential growth, interpersonal communication has come to play an increasingly central role in opinion formation and change. In order help users better engage with each other online, we study a challenging problem of re-entry prediction foreseeing whether user will back conversation they once participated in. We hypothesize that both context ongoing conversations users' previous chatting history affect their continued interests future engagement. Specifically, propose neural framework three main layers, modeling context, history, interactions between them, explore how jointly result behavior. experiment two large-scale datasets collected from Twitter Reddit. Results show our proposed bi-attention achieves F1 score 61.1 on conversations, outperforming state-of-the-art methods work.