3 research outputs found
Characterizing and Predicting Email Deferral Behavior
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