Characterizing Reading Time on Enterprise Emails
Email is an integral part of people's work and life, enabling them to perform activities such as communicating, searching, managing tasks and storing information. Modern email clients take a step forward and help improve users' productivity by automatically creating reminders, tasks or responses. The act of reading is arguably the only activity that is in common in most -- if not all -- of the interactions that users have with their emails. In this paper, we characterize how users read their enterprise emails, and reveal the various contextual factors that impact reading time. Our approach starts with a reading time analysis based on the reading events from a major email platform, followed by a user study to provide explanations for some discoveries. We identify multiple temporal and user contextual factors that are correlated with reading time. For instance, email reading time is correlated with user devices: on desktop reading time increases through the morning and peaks at noon but on mobile it increases through the evening till midnight. The reading time is also negatively correlated with the screen size. We have established the connection between user status and reading time: users spend more time reading emails when they have fewer meetings and busy hours during the day. In addition, we find that users also reread emails across devices. Among the cross-device reading events, 76% of reread emails are first visited on mobile and then on desktop. Overall, our study is the first to characterize enterprise email reading time on a very large scale. The findings provide insights to develop better metrics and user models for understanding and improving email interactions.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
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 com…
Holmes: An Efficient and Lightweight Semantic Based Anomalous Email Detector
Email threat is a serious issue for enterprise security, which consists of various malicious scenarios, such as phishing, fraud, blackmail and malvertisement. Traditional anti-spam gateway commonly requires to maintain a…
Anomaly DetectionNovelty DetectionSentenceSay ‘YES’ to Positivity: Detecting Toxic Language in Workplace Communications
Workplace communication (e.g. email, chat, etc.) is a central part of enterprise productivity. Healthy conversations are crucial for creating an inclusive environment and maintaining harmony in an organization. Toxic com…
Characterizing and Predicting Enterprise Email Reply Behavior
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 informati…
Analyzing Social and Stylometric Features to Identify Spear phishing Emails
Spear phishing is a complex targeted attack in which, an attacker harvests information about the victim prior to the attack. This information is then used to create sophisticated, genuine-looking attack vectors, drawing …