and Retrieval – information filtering

Twitter has redefined the way social activities can be coordinated; used for mobilizing people during natural disasters, studying health epidemics, and recently, as a communication platform during social and political change. As a large scale system, the volume of data transmitted per day presents Twitter users with a problem: how can valuable content be distilled from the back chatter, how can the providers of valuable information be promoted, and ultimately how can influential individuals be identified? To tackle this, we have developed a model based upon the Twitter message exchange which enables us to analyze conversations around specific topics and identify key players in a conversation. A working implementation of the model helps categorize Twitter users by specific roles based on their dynamic communication behavior rather than an analysis of their static friendship network. This provides a method of identifying users who are potentially producers or distributers of valuable knowledge