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Discourse relations in rationale‐containing text‐segments
Author(s) -
Xiao Lu,
Conroy Nadia K.
Publication year - 2017
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23882
Subject(s) - generalizability theory , computer science , leverage (statistics) , perspective (graphical) , sample (material) , face (sociological concept) , empirical research , discourse analysis , face to face interaction , data science , artificial intelligence , linguistics , sociology , psychology , epistemology , communication , developmental psychology , chemistry , philosophy , chromatography
Offering one's perspective and justifying it has become a common practice in online text‐based communications, just as it is in typical, face‐to‐face communication. Compared to the face‐to‐face communications, it can be particularly more challenging for users to understand and evaluate another's perspective in online communications. On the other hand, the availability of the communication record in online communications offers a potential to leverage computational techniques to automatically detect user opinions and rationales. One promising approach to automatically detect the rationales is to detect the common discourse relations in rationale texts. However, no empirical work has been done with regard to which discourse relations are commonly present in the users’ rationales in online communications. To fill this gap, we annotated the discourse relations in the text segments that contain the rationales ( N = 527 text segments). These text segments are obtained from five datasets that consist of five online posts and the first 100 comments. We identified 10 discourse relations that are commonly present in this sample. Our finding marks an important contribution to this rationale detection approach. We encourage more empirical work, preferably with a larger sample, to examine the generalizability of our findings.