How useful are semantic links for the detection of implicit references in CSCL chats?

Abstract

Chat conversations are used for a large range of Computer-Supported Collaborative Learning (CSCL) tasks especially because they allow the creation of multiple conversation threads that run in parallel. Thus, several different topics can be debated at the same time, fostering the exploitation of different ideas and facilitating collaborative knowledge creation. In order to detect these threads, our method proposed to firstly detect the links that arise between the utterances of a conversation. From a computational linguistics perspective, there is a wide variety of different types of links between utterances and there is no mechanism to compute all of them. This paper proposes to explain to what degree semantic similarity measures from Natural Language Processing (NLP) may be used to detect the links that arise between utterances in CSCL chat conversations and which is the effectiveness of applying solely this technique for implicit links identification.