Abstract

In this work we examine the characteristics of social activity and patterns of communication on Twitter, a prominent example of the emerging class of communication systems we call “social awareness streams. ” We use system data and message content from over 350 Twitter users, applying human coding and quantitative analysis to provide a deeper understanding of the activity of individuals on the Twitter network. In particular, we develop a content-based categorization of the type of messages posted by Twitter users, based on which we examine users ’ activity. Our analysis shows two common types of user behavior in terms of the content of the posted messages, and exposes differences between users in respect to these activities.

Citations