Conference Proceeding Article
We explore Debatepedia, a communityauthored encyclopedia of sociopolitical debates, as evidence for inferring a lowdimensional, human-interpretable representation in the domain of issues and positions. We introduce a generative model positing latent topics and cross-cutting positions that gives special treatment to person mentions and opinion words. We evaluate the resulting representation’s usefulness in attaching opinionated documents to arguments and its consistency with human judgments about positions.
Databases and Information Systems | Numerical Analysis and Scientific Computing
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Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, Seattle, Washington, 18-21 October 2013
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GOTTOPATI, Swapna; QIU, Minghui; SIM, Yanchuan; JIANG, Jing; and SMITH, Noah.
Learning Topics and Positions from Debatepedia. (2013). Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, Seattle, Washington, 18-21 October 2013. 1858-1868. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2059
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.