A CS+Linguistics group of collaborators — Su Lin Blodgett (CS), Lisa Green (Linguistics), and Brendan O’Connor (CS) — have published a paper on African-American English and Twitter. It will be presented at Empirical Methods in Natural Language Processing this November, and published in the Proceedings of EMNLP. A preprint is linked below.

Demographic Dialectal Variation in Social Media: A Case Study of African-American English

Abstract:
Though dialectal language is increasingly abundant on social media, few resources exist for developing NLP tools to handle such language. We conduct a case study of dialectal language in online conversational text by investigating African-American English (AAE) on Twitter. We propose a distantly supervised model to identify AAE-like language from demographics associated with geo-located messages, and we verify that this language follows well-known AAE linguistic phenomena. In addition, we analyze the quality of existing language identification and dependency parsing tools on AAE-like text, demonstrating that they perform poorly on such text compared to text associated with white speakers. We also provide an ensemble classifier for language identification which eliminates this disparity and release a new corpus of tweets containing AAE-like language.