Multilingual individuals code switch between languages as a part of a complex communication process. However, most computational studies have examined only one or a handful of contextual factors predictive of switching. Here, we examine Naijá-English code switching in a rich contextual environment to understand the social and topical factors eliciting a switch. We introduce a new corpus of 330K articles and accompanying 389K comments labeled for code switching behavior. In modeling whether a comment will switch, we show that topic-driven variation, tribal affiliation, emotional valence, and audience design all play complementary roles in behavior.
CITATION STYLE
Ndubuisi-Obi, I., Ghosh, S., & Jurgens, D. (2020). Wétin dey with these comments? Modeling sociolinguistic factors affecting code-switching behavior in nigerian online discussions. In ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (pp. 6204–6214). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p19-1625
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