Emma Spiro


2017

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Non-lexical Features Encode Political Affiliation on Twitter
Rachael Tatman | Leo Stewart | Amandalynne Paullada | Emma Spiro
Proceedings of the Second Workshop on NLP and Computational Social Science

Previous work on classifying Twitter users’ political alignment has mainly focused on lexical and social network features. This study provides evidence that political affiliation is also reflected in features which have been previously overlooked: users’ discourse patterns (proportion of Tweets that are retweets or replies) and their rate of use of capitalization and punctuation. We find robust differences between politically left- and right-leaning communities with respect to these discourse and sub-lexical features, although they are not enough to train a high-accuracy classifier.