Using Function Words for Authorship Attribution: Bag-Of-Words vs. Sequential Rules
Author(s) -
Mohamed Amine Boukhaled,
JeanGabriel Ganascia
Publication year - 2015
Publication title -
natural language processing and cognitive science
Language(s) - English
Resource type - Book series
DOI - 10.1515/9781501501289.115
Subject(s) - attribution , function (biology) , authorship attribution , task (project management) , style (visual arts) , natural language processing , set (abstract data type) , computer science , artificial intelligence , word (group theory) , linguistics , psychology , social psychology , engineering , history , biology , programming language , evolutionary biology , philosophy , systems engineering , archaeology
International audienceAuthorship attribution is the task of identifying the author of a given document. Various style markers have been proposed in the literature to deal with the authorship attribution task. Frequencies of function words have been shown to be very reliable and effective for this task. However, despite the fact that they are state-of-the-art, they basically rely on the invalid bag-of-words assumption, which stipulates that text is a set of independent words. In this contribution, we present a comparative study on using two different types of style marker based on function words for authorship attribution. We compare the effectiveness of using sequential rules of function words as style marker that do not relay on the bag-of-words assumption to that of the frequency of function words which does. Our results show that the frequencies of function words outperform the sequential rules
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