SIGIR 2017 Paper Characterizing and Predicting Enterprise Email Reply Behavior

中文简介：本文对企业邮件系统中的用户行为进行了建模分析，首先分析了影响用户邮件回复行为的几类因素，然后基于分析结果建立了预测用户邮件回复行为和邮件回复时间的机器学习模型。基于Avocado邮件数据的实验结果表明，本文提出的特征和模型对于用户邮件回复行为的预测准确度大幅度超过了以往的基准方法。
论文出处：SIGIR'17

英文摘要：Email is still among the most popular online activities. People spend a significant amount of time sending, reading and responding to email in order to communicate with others, manage tasks and archive personal information. Most previous research on email is based on either relatively small data samples from user surveys and interviews, or on consumer email accounts such as those from Yahoo!  Mail or Gmail. Much less has been published on how people interact with enterprise email even though it contains less automatically generated commercial email and involves more organizational behavior than is evident in personal accounts. In this paper, we extend previous work on predicting email reply behavior by looking at enterprise settings and considering more than dyadic communications. We characterize the influence of various factors such as email content and metadata, historical interaction features and temporal features on email reply behavior. We also develop models to predict whether a recipient will reply to an email and how long it will take to do so. Experiments with the publicly-available Avocado email collection show that our methods outperform all baselines with large gains. We also analyze the importance of different features on reply behavior predictions. Our findings provide new insights about how people interact with enterprise email and have implications for the design of the next generation of email clients.

下载链接：http://ciir-publications.cs.umass.edu/getpdf.php?id=1270
实验数据链接：https://sites.google.com/site/lyangwww/code-data