• DocumentCode
    660790
  • Title

    Finding Participants in a Chat: Authorship Attribution for Conversational Documents

  • Author

    Inches, Giacomo ; Harvey, Matthew ; Crestani, Fabio

  • Author_Institution
    Fac. of Inf., Univ. of Lugano (USI), Lugano, Switzerland
  • fYear
    2013
  • fDate
    8-14 Sept. 2013
  • Firstpage
    272
  • Lastpage
    279
  • Abstract
    In this work we study the problem of Authorship Attribution for a novel set of documents, namely online chats. Although the problem of Authorship Attribution has been extensively investigated for different document types, from books to letters and from emails to blog posts, to the best of our knowledge this is the first study of Authorship Attribution for conversational documents (IRC chat logs) using statistical models. We experimentally demonstrate the unsuitability of the classical statistical models for conversational documents and propose a novel approach which is able to achieve a high accuracy rate (up to 95%) for hundreds of authors.
  • Keywords
    document handling; interactive programming; social networking (online); statistical analysis; IRC chat logs; authorship attribution; conversational documents; online chats; statistical models; Equations; Maximum likelihood estimation; Media; Smoothing methods; Standards; Training; Vocabulary; authorship attribution; conversational documents; irc chats; text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Computing (SocialCom), 2013 International Conference on
  • Conference_Location
    Alexandria, VA
  • Type

    conf

  • DOI
    10.1109/SocialCom.2013.45
  • Filename
    6693342