描述和预测电子邮件延迟行为
Characterizing and Predicting Email Deferral Behavior
摘要：
电子邮件分流涉及通过未处理的电子邮件，并决定如何处理它们。随着未处理电子邮件数量的增加，这个熟悉的过程可能变得越来越具有挑战性。在分流会话期间，用户通常会推迟处理他们无法立即处理的电子邮件。这些延迟的电子邮件通常与推迟的任务有关，直到用户有更多的时间或正确的信息来处理它们。本文通过定性访谈和大规模的日志分析，研究了企业电子邮件用户倾向于推迟的时间和内容。我们发现，当处理电子邮件涉及回复、仔细阅读或点击链接和附件时，用户更有可能推迟处理电子邮件。我们还了解到，决定推迟电子邮件取决于许多因素，如用户的工作量和发件人的重要性。我们的定性结果表明，延迟是非常普遍的，我们的定量日志分析证实，12%的分流会话和16%的日常活跃用户在工作日至少有一个延迟的电子邮件。我们还讨论了几个延迟策略，如标记为未读的电子邮件和标记，我们的受访者报告，并说明如何也可以在用户日志中观察到这样的模式。受延迟电子邮件的特性和决定电子邮件是否应该延迟的上下文因素的启发，我们训练分类器来预测最近分类的电子邮件是否实际上被延迟。我们的实验结果表明，推迟可以归类为适度的有效性。总的来说，我们的工作提供了关于用户如何处理他们的电子邮件以及如何延迟建模的新见解。
英文摘要：
Email triage involves going through unhandled emails and deciding what to do with them. This familiar process can become increasingly challenging as the number of unhandled email grows. During a triage session, users commonly defer handling emails that they cannot immediately deal with to later. These deferred emails, are often related to tasks that are postponed until the user has more time or the right information to deal with them. In this paper, through qualitative interviews and a large-scale log analysis, we study when and what enterprise email users tend to defer. We found that users are more likely to defer emails when handling them involves replying, reading carefully, or clicking on links and attachments. We also learned that the decision to defer emails depends on many factors such as user's workload and the importance of the sender. Our qualitative results suggested that deferring is very common, and our quantitative log analysis confirms that 12% of triage sessions and 16% of daily active users had at least one deferred email on weekdays. We also discuss several deferral strategies such as marking emails as unread and flagging that are reported by our interviewees, and illustrate how such patterns can be also observed in user logs. Inspired by the characteristics of deferred emails and contextual factors involved in deciding if an email should be deferred, we train a classifier for predicting whether a recently triaged email is actually deferred. Our experimental results suggests that deferral can be classified with modest effectiveness. Overall, our work provides novel insights about how users handle their emails and how deferral can be modeled.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
