Modeling User Behavior in Adoption and Diffusion of Twitter Clients

With the onset of ubiquitous social media technology, people leave numerous traces of their social behavior in - often publicly available - data sets. In this paper we look at a virtual community of independent ("Indie") software developers for the Macintosh and iPhone that use the social networking site Twitter. Using Twitter's API, we collect longitudinal data on network connections among the In die developers and their friends and followers (approximately15.000 nodes) and their Twitter behavior over a period of five weeks (more than 600.000 "tweets"). We use this dynamic data on the network and user behavior to analyze the adoption of Twitter client software.