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2016
Conference Paper
Title
Supervised speech act classification of messages in german online discussions
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.
Author(s)