Mining Chat-room Conversations for Social and Semantic Interactions

Abstract

The ephemeral nature of human communication via networks today poses interesting and challenging problems for information technologists. The Intelink intelligence network, for example, has a need to monitor chat-room conversations to ensure the integrity of sensitive data being transmitted via the network. However, the sheer volume of communication in venues such as email, newsgroups, and chat precludes manual techniques of information management. It has been estimated that over 430 million instant messages, for example, are exchanged each day on the America Online network [3].