Paper: Political Ideology Detection Using Recursive Neural Networks

ACL ID P14-1105
Title Political Ideology Detection Using Recursive Neural Networks
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

An individual?s words often reveal their po- litical ideology. Existing automated tech- niques to identify ideology from text focus on bags of words or wordlists, ignoring syn- tax. Taking inspiration from recent work in sentiment analysis that successfully models the compositional aspect of language, we apply a recursive neural network (RNN) framework to the task of identifying the po- litical position evinced by a sentence. To show the importance of modeling subsen- tential elements, we crowdsource political annotations at a phrase and sentence level. Our model outperforms existing models on our newly annotated dataset and an existing dataset.