Andrew Fiore, Scott Counts, and Marc A. Smith
In this paper we describe an evaluation of behavioral descriptors generated from an analysis of a large collection of Usenet newsgroup messages. The metrics describe aspects of newsgroup authors’ behavior over time; such information can aid in filtering, sorting, and recommending content from public discussion spaces like newsgroups. To assess the value of a variety of these behavioral descriptors, we compared 22 participants’ subjective evaluations of authors whose messages they read to behavioral metrics describing the same authors. We found that many metrics, particularly the longevity and frequency of participation, the number of newsgroups to which authors contribute messages, and the amount they contribute to each thread, correlate highly with readers’ subjective evaluations of the authors.
|Publisher||Association for Computing Machinery, Inc.|
Copyright © 2004 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or email@example.com. The definitive version of this paper can be found at ACM’s Digital Library –http://www.acm.org/dl/.