Computer-mediated communication (CMC) systems such as Usenet newsgroups, e-mail lists, online chats, etc. facilitate large-scale human interactions and produce large sets of activity records. These datasets can be used to analyze and visualize the social networks exist at the online forums. Such analyses often improve our understanding of online inter-personal interactions, as well as lead to better designs and implementations of CMC systems.

We report in this paper our experience in designing a newsgroup browser based on ideas from social network analysis. Our analyzer identifies reciprocal sub-groups in newsgroup discussions, and utilizes visual methods to help users look for leading authors and provocative articles. This is especially helpful for late comers to catch up and participate in popular and noisy newsgroups.