Authorship recognition in a multiparty chat scenario

Rldvan Salih Kuzu, Koray Balci, Albert Ali Salah

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

Abstract

Users of online social networks often use multiple identities. This paper investigates the possibility of identifying a user from his or her chat behavior in such a setting. We have collected a large corpus of multiparty chat records in Turkish, obtained from a multiplayer game database. The most active 978 users are selected according to their participation in game chat sessions. This corpus is used in a biometric identification experiment where we seek each user among a gallery of users. Character matrices for each player are used as features, and re-centered local profiles and cosine similarity measure are preferred as identification methods. We systematically assess the effect of text normalization on identification. We report comparative results, the best of which reach around 75% rank-1 accuracy for a gallery size of 978.

Original languageEnglish
Title of host publicationProceedings - 2016 4th International Workshop on Biometrics and Forensics, IWBF 2016
PublisherIEEE
ISBN (Electronic)9781467394482
DOIs
Publication statusPublished - 7 Apr 2016
Event4th International Workshop on Biometrics and Forensics, IWBF 2016 - Limassol, Cyprus
Duration: 3 Mar 20164 Mar 2016

Conference

Conference4th International Workshop on Biometrics and Forensics, IWBF 2016
Country/TerritoryCyprus
CityLimassol
Period3/03/164/03/16

Funding

This work is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) with project number 114E481 and by the Turkish Ministry of Development under the TAM Project number DPT2007K120610

Keywords

  • Authorship recognition
  • Chat biometrics
  • Chat mining
  • Machine learning
  • Multiparty chat
  • Text classification
  • Text information retrieval

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