Political Ideology Detection Using Recursive Neural Networks

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.