Date of Original Version

10-2013

Type

Conference Proceeding

Journal Title

Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP)

First Page

91

Last Page

101

Rights Management

Copyright 2013 Association for Computational Linguistics

Abstract or Description

We seek to measure political candidates’ ideological positioning from their speeches. To accomplish this, we infer ideological cues from a corpus of political writings annotated with known ideologies. We then represent the speeches of U.S. Presidential candidates as sequences of cues and lags (filler distinguished only by its length in words). We apply a domain-informed Bayesian HMM to infer the proportions of ideologies each candidate uses in each campaign. The results are validated against a set of preregistered, domain expertauthored hypotheses.

Share

COinS
 

Published In

Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 91-101.