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
Link To Document