Using frequency-of-mention in public conversations for social filtering

Will Hill, Loren Terveen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

31 Scopus citations

Abstract

We report on an investigation of using Usenet newsgroups for social filtering of Web resources. Our main empirical results are: (1) for the period of May '96 to Jul '96, about 23% of Usenet news messages mention Web resources, (2) 19% of resource mentions are recommendations (as opposed, e.g., to home pages), (3) we can automatically recognize recommendations with at least 90% accuracy, and (4) in some newsgroups, certain resources are mentioned significantly more frequently than others and thus appear to play a central role for that community. We have created a Web site that summarizes the most frequently and recently mentioned Web resources for 1400 newsgroups.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM Conference on Computer Supported Cooperative Work
Editors Anon
PublisherACM
Pages106-112
Number of pages7
StatePublished - Dec 1 1996
EventProceedings of the 1996 ACM Conference on Computer Supported Cooperative Work, CSCW - Boston, MA, USA
Duration: Nov 16 1996Nov 20 1996

Other

OtherProceedings of the 1996 ACM Conference on Computer Supported Cooperative Work, CSCW
CityBoston, MA, USA
Period11/16/9611/20/96

Fingerprint Dive into the research topics of 'Using frequency-of-mention in public conversations for social filtering'. Together they form a unique fingerprint.

Cite this