Learning Topics and Positions from Debatepedia

Learning Topics and Positions from Debatepedia

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 spec...

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Bibliographic Details
Main Authors: GOTTOPATI, Swapna, QIU, Minghui, SIM, Yanchuan, JIANG, Jing, SMITH, Noah
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2013
Subjects:
Databases and Information Systems
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/2059
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=3058&context=sis_research
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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