Email is a ubiquitous communications tool in the workplace and plays an important role in social interactions. Previous studies of email were largely based on surveys and limited to relatively small populations of email users within organizations. In this paper, we report results of a large-scale study of more than 2 million users exchanging 16 billion emails over several months. We quantitatively characterize the replying behavior in conversations within pairs of users. In particular, we study the time it takes the user to reply to a received message and the length of the reply sent. We consider a variety of factors that affect the reply time and length, such as the stage of the conversation, user demographics, and use of portable devices. In addition, we study how increasing load affects emailing behavior. We find that as users receive more email messages in a day, they reply to a smaller fraction of them, using shorter replies. However, their responsiveness remains intact, and they may even reply to emails faster. Finally, we predict the time to reply, length of reply, and whether the reply ends a conversation. We demonstrate considerable improvement over the baseline in all three prediction tasks, showing the significant role that the factors that we uncover play, in determining replying behavior. We rank these factors based on their predictive power. Our findings have important implications for understanding human behavior and designing better email management applications for tasks like ranking unread emails.
Quantitative studies targeted to specific application-oriented tasks such as classification of emails into folders @cite_23 @cite_27 were conducted mainly on the open Enron email data @cite_11 , which is one of the few complete temporal data on email communication whose structure has been studied extensively @cite_34 . However, Enron's email communication patterns were very specific as they were limited to the context of the company and by its evolution and dramatic fall. This peculiarity held back researchers from drawing conclusions on general patterns of email use. Other less known, small-scale email datasets, such as the email corpora from OSS projects @cite_37 can provide interesting traces on user interaction, but they do not allow any generalization of the findings. Email communication networks have been also used to investigate the propagation of computer viruses @cite_16 and word-of-mouth advertising @cite_21 , or to solve specific tasks such as expert finding within organizations @cite_32 .
@cite_37 @cite_21 @cite_32 @cite_16 @cite_27 @cite_23 @cite_34 @cite_11
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A large set of email messages, the Enron corpus, was made public during the legal investigation concerning the Enron corporation. This dataset, along with a thorough explanation of its origin, is available at http: www-2.cs.cmu.edu enron . This paper provides a brief introduction and analysis of the dataset. The raw Enron corpus contains 619,446 messages belonging to 158 users. We cleaned the corpus before this analysis by removing certain folders from each user, such as “discussion_threads”. These folders were present for most users, and did not appear to be used directly by the users, but rather were computer generated. Many, such as “all_documents”, also contained large numbers of duplicate emails, which were already present in the users’ other folders. Our goal in this paper is to analyze the suitability of this corpus for exploring how to classify messages as organized by a human, so these folders would have likely been misleading. We investigate the structures present in the Enron email dataset using singular value decomposition and semidiscrete decomposition. Using word frequency profiles, we show that messages fall into two distinct groups, whose extrema are characterized by short messages and rare words versus long messages and common words. It is surprising that length of message and word use pattern should be related in this way. We also investigate relationships among individuals based on their patterns of word use in email. We show that word use is correlated to function within the organization, as expected. Lastly, we show that relative changes to individuals' word usage over time can be used to identify key players in major company events. Email logs have been considered as a useful resource for research in fields like link analysis, social network analysis and textual analysis. Most of the experiments in these fields of research are performed on synthetic data due to lack of an adequate and real life benchmark. The Enron email dataset is a touchstone for such research. This dataset is very similar to the kind of the data collected for fraud detection and counter terrorism hence it is a perfect test bed for testing the effectiveness of techniques used for counter terrorism and fraud detection. In this report we describe the MySql database prepared for the dataset and also statistically analyze its appropriateness for research. We further derive a social network constituting of 151 employees from the email logs, by defining a social contact to be someone with whom an individual has exchanged a pre decided threshold number of emails. The Enron email corpus is appealing to researchers because it represents a rich temporal record of internal communication within a large, real-world organization facing a severe and survival-threatening crisis. We describe how we enhanced the original corpus database and present findings from our investigation undertaken with a social network analytic perspective. We explore the dynamics of the structure and properties of the organizational communication network, as well as the characteristics and patterns of communicative behavior of the employees from different organizational levels. We found that during the crisis period, communication among employees became more diverse with respect to established contacts and formal roles. Also during the crisis period, previously disconnected employees began to engage in mutual communication, so that interpersonal communication was intensified and spread through the network, bypassing formal chains of communication. The findings of this study provide valuable insight into a real-world organizational crisis, which may be further used for validating or developing theories and dynamic models of organizational crises; thereby leading to a better understanding of the underlying causes of, and response to, organization failure.