Learning Topics and Positions from Debatepedia
Swapna Sri Gottipati, Minghui Qiu, Yanchuan Sim, Jing Jiang, Noah A. Smith · 2013
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.0.1 0.2 0.3 0.4 0.5 comment, minimum, wage, poverty, capitalism nuclear, weapons, iran, states, threat party, vote, republican, political, voters energy, gas, power, fuel, wind