A Multilevel Text Processing Model of Newsgroup Dynamics

We present a multilevel model of discussions in USENET newsgroups that includes the use of statistical and linguistic methods to obtain lexical, semantic and discourse characteristics of the text. We expose constraints that make information extraction and summarization more amenable to analysis at different levels. Our model makes use of posting structure, times of posting, time spans, and length and depth of a thread in order to extract higher-level information on subject matter, interest level, topicality, and discussion trends.