Stance Classification on Short Text Comments in Chinese
Date Issued
2016
Date
2016
Author(s)
Chuang, Ju-Han
Abstract
With the development of social networking services, information sharing and the form of media have been revolutionized. Each of us might be part of the reason why certain movements are able to take place, why several issues are finally noticed by the public, and how a video or a piece of work goes viral. What we say or do on the Internet has its influence on others, and leave traces that we can observe. Thus gave rise to studies that aim at understanding online behaviors. From a linguistic point of view, we find it worthwhile to observe how people take a stance online and their attempts to persuade others. The current study aims at observing stance-taking behavior on short comments on PTT in order to establish resources on “linguistic cues” that reveal a speaker’s overall position on an article or on a proposition. Subjective cues and arguing cues are identified from extracted PTT positive and negative comments. The cues are then used to assist in automated stance classification to compare with baseline performance. Results indicate that the cues can help raise up to 20 percent of accuracy. The classifier can be better improved with larger tagging set and techniques that can identify context in future work.
Subjects
PTT
stance classification
pragmatics
corpus-linguistics
online comments
Type
thesis
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