Effective email network visualization techniques by means of user behaviors

摘要

In email or twitter networks, mining interaction behaviors of actors is a useful task in viral marketing or targeted advertisement. In this work, we define two interaction behaviors. One is engagingness representing the ability of soliciting active response for an initiated message. The other is responsiveness that indicates the ability of responding to an incoming message in information exchange networks. To study such behaviors, we make use of Enron email data set that are so far the only known publicly available information exchange data with messages assigned with specific senders and recipients. We also conduct data preprocessing on the email data and establish links between emails and their replies. Then, we propose quantitative behavior models for systematically measuring each user's engagingness and responsiveness scores in the email network. Further we present a graph visualization technique in order to visualize information exchange networks by means of the concept of behaviors and community structures. In our empirical study, we compare the proposed behavior models, and introduce several properties of behaviors out which we found with the Enron email data set. In addition, our visualization technique will be better able to figure out the underlying characteristics of information exchange networks based on our behavior models.