That’s your evidence?: Classifying Stance in Online Political Debate
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Authors
Walker, Marilyn A.
Anand, Pranav
Abbott, Rob
Fox Tree, Jean E.
Martell, Craig
King, Joseph
Subjects
online debate
argumentation strategies
dialogue
stance
automatic classification
argumentation strategies
dialogue
stance
automatic classification
Advisors
Date of Issue
2012
Date
Publisher
Elsevier B.V.
Language
Abstract
A growing body of work has highlighted the challenges of identifying the stance that a speaker holds towards a particular topic, a task that involves identifying a holistic subjective disposition. We examine stance classification on a corpus of 4731 posts from the debate website ConvinceMe.net, for 14 topics ranging from the playful to the ideological. We show that ideological debates feature a greater share of rebuttal posts, and that rebuttal posts are significantly harder to classify for stance, for both humans and trained classifiers. We also demonstrate that the number of subjective expressions varies across debates, a fact correlated with the performance of systems sensitive to sentiment-bearing terms. We present results for classifying stance on a per topic basis that range from 60% to 75%, as compared to unigram baselines that vary between 47% and 66%. Our results suggest that features and methods that take into account the dialogic context of such posts improve accuracy.
Type
Article
Description
The article of record may be found at https://doi.org/10.1016/j.dss.2012.05.032
Funded by Naval Postgraduate School
The article of record as published may be found at https://doi.org/10.1016/j.ijpe.2020.107840
Funded by Naval Postgraduate School
The article of record as published may be found at https://doi.org/10.1016/j.ijpe.2020.107840
Series/Report No
Funded by Naval Postgraduate School
Department
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
This work was funded by Naval Postgraduate School Grant NPS- BAA-03 to UCSC, and by the Intelligence Advanced Research Projects Activity (IARPA) through the Army Research Laboratory.
Funder
This work was funded by Naval Postgraduate School Grant NPS- BAA-03 to UCSC, and by the Intelligence Advanced Research Projects Activity (IARPA) through the Army Research Laboratory.
Format
11 p.
Citation
Walker, Marilyn A., et al. "That’s your evidence?: Classifying stance in online political debate." Decision Support Systems 53.4 (2012): 719-729.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.