Non-lexical features encode political affiliation on twitter

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Abstract

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.

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APA

Tatman, R., Paullada, A., Stewart, L. G., & Spiro, E. S. (2017). Non-lexical features encode political affiliation on twitter. In Proceedings of the 2nd Workshop on Natural Language Processing and Computational Social Science, NLP+CSS 2017 at the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 (pp. 63–67). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-2909

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