论文标题
用户脱离接触预测的生存分析：问答社区的案件
Survival analysis for user disengagement prediction: question-and-answering communities' case
论文作者
论文摘要
我们使用生存分析在这项工作中的三个不同的问题和吸引社区中为用户脱离接触进行了建模。我们使用{政治，数据科学，计算机科学}的完整历史数据从成立到2021年5月，其中包括有关这三个社区之一的所有用户的信息。此外，将用户脱离接触预测作为一项生存分析任务，我们利用两种生存分析技术来建模和预测每个社区成员的概率。我们的主要发现是，甚至有几个贡献保持活跃的用户的可能性明显高于没有做出贡献的用户。随着时间的流逝，这种区别可能会扩大。此外，我们的实验结果表明，对平台上共享的内容的看法更有利的用户可能会停留更长的时间。最后，观察到的模式适用于所有三个社区，无论其主题如何。
We used survival analysis to model user disengagement in three distinct questions-and-answering communities in this work. We used the complete historical data of {Politics, Data Science, Computer Science} Stack Exchange communities from their inception until May 2021, which include the information about all users who were members of one of these three communities. Furthermore, formulating the user disengagement prediction as a survival analysis task, we utilised two survival analysis techniques to model and predict the probabilities of members of each community becoming disengaged. Our main finding is that the likelihood of users with even a few contributions staying active is noticeably higher than the users who were making no contributions; this distinction may widen as time passes. Moreover, the results of our experiments indicate that users with more favourable views towards the content shared on the platform may stay engaged longer. Finally, the observed pattern holds for all three communities, regardless of their themes.
