TY - JOUR
T1 - Discourse relations in rationale-containing text-segments
AU - Xiao, Lu
AU - Conroy, Niall
N1 - Funding Information:
We thank Dianhong Lu for his assistance in annotating the rationales. This project is partially supported by the Discovery program of Natural Sciences and Engineering Research Council of Canada (NSERC).
Publisher Copyright:
© 2017 ASIS&T.
PY - 2017/9
Y1 - 2017/9
N2 - 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.
AB - 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.
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U2 - 10.1002/asi.23882
DO - 10.1002/asi.23882
M3 - Article
AN - SCOPUS:85030111298
SN - 2330-1635
VL - 68
SP - 2783
EP - 2794
JO - Journal of the Association for Information Science and Technology
JF - Journal of the Association for Information Science and Technology
IS - 12
ER -