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Supervised speech act classification of messages in german online discussions

 
: Bayat, Berken; Krauss, Christopher; Merceron, Agathe; Arbanowski, Stefan

Markov, Zdravko (Ed.) ; Florida Artificial Intelligence Research Society -FLAIRS-; Association for the Advancement of Artificial Intelligence -AAAI-:
29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016. Proceedings : Key Largo, Florida, May 16-18, 2016
Menlo Park: AAAI Press, 2016
ISBN: 978-1-57735-756-8
S.204-209
International Florida Artificial Intelligence Research Society Conference (FLAIRS) <29, 2016, Key Largo/Fla.>
Englisch
Konferenzbeitrag
Fraunhofer FOKUS ()
NLP; SVM; ITS

Abstract
University lectures often offer online discussion forums for students to discuss and solve issues with other students and instructors. Correlating the participation of a student in a discussion forum to his performance in the course is subject of current research. Therefore, to qualify the different parts a student plays in a discussion, be it asking or answering a question, is sought in this paper. In current analysis of online discussion forums, such parts are annotated by hand. Thereby, identifying corresponding roles manually is a costly task, which requires the work of more than one person to annotate and approve the chosen roles. The desired step to a better understanding of student online discussion forums is the automated annotation of student roles. A student's role is determined by classifying the student's message into different speech act categories. This paper introduces a supervised speech act classification method for messages in German discussion forums that aims at solving the problem of manually detecting speech acts in online discussion for further discourse analysis. A comparative evaluation shows the significant improvements of the new classifier and its appropriateness for the German language.

: http://publica.fraunhofer.de/dokumente/N-399487.html