Characterizing Attitudinal Behaviors in On-Line Open-Sources

Richard M. Tong and Ronald R. Yager

On-line public discussions, such as newsgroups, message boards, and other similar forums, are an under-exploited but potentially valuable resource in developing analyses of world events. An effective way of characterizing this large volume of information is to create time-series that represent the subjects, opinions, and attitudes expressed in these sources. Automatically generated "Linguistic Descriptions" then provide natural and easily understood summaries of the behaviors exhibited by these time series. In this extended abstract, we describe preliminary work on the development of a prototype system to implement our concept of Linguistic Descriptions applied to the attitudinal behaviors seen in on-line discussion forums and news sources.

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.