Detecting conversing groups of chatters: a model, algorithms, and tests

Chatrooms, for example Internet Relay Chat, are gen erally multi-user, multi-channel and multi-server c hat-systems, which run over the Internet and provide a protocol for real-time text-based conferencing between users all over the world. While a well-trained human observer is able to unde rstand who is chatting with whom, there are no effi cient and accurate automated tools to determine the groups of users co nversing with each other. A precursor to analyze ev olving cybersocial phenomena is to first determine what the con versations are and which groups of chatters are inv olved in each conversation. We consider this problem in this pape r. We propose an algorithm to discover all groups o f users that are engaged in conversation. Our algorithms are based o n a statistical model of a chatroom that is founded on our experience with real chatrooms. Our approach does not require any semantic analysis of the conversations; rather it is based purely on the statistical information contained in the seq uence of posts. We improve the accuracy by applying some graph algorithms to clean the statistical information. We present some experimental results, which indicate that one can automatically determine the conversing groups in a chatroom, purely on the basis of statistical analys is. KEYWORDS social networks, conversing groups, IRC, chatters, chatrooms, chatroom model. 1