Authorship attribution with thousands of candidate authors

Moshe Koppel, Jonathan Schier, Shlomo Argamon, Eran Messeri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

69 Scopus citations

Abstract

In this paper, we use a blog corpus to demonstrate that we can often identify the author of an anonymous text even where there are many thousands of candidate authors. Our approach combines standard information retrieval methods with a text categorization meta-learning scheme that determines when to even venture a guess.

Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery
Pages659-660
Number of pages2
ISBN (Print)1595933697, 9781595933690
DOIs
StatePublished - 2006
Event29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - Seatttle, WA, United States
Duration: 6 Aug 200611 Aug 2006

Publication series

NameProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Volume2006

Conference

Conference29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Country/TerritoryUnited States
CitySeatttle, WA
Period6/08/0611/08/06

Keywords

  • Authorship attribution
  • Blog analysis

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