@inproceedings{kantharaju-schmer-galunder-2022-extracting,
    title = "Extracting Associations of Intersectional Identities with Discourse about Institution from {N}igeria",
    author = "Kantharaju, Pavan  and
      Schmer-galunder, Sonja",
    editor = "Bamman, David  and
      Hovy, Dirk  and
      Jurgens, David  and
      Keith, Katherine  and
      O'Connor, Brendan  and
      Volkova, Svitlana",
    booktitle = "Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS)",
    month = nov,
    year = "2022",
    address = "Abu Dhabi, UAE",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.nlpcss-1.18/",
    doi = "10.18653/v1/2022.nlpcss-1.18",
    pages = "164--169",
    abstract = "Word embedding models have been used in prior work to extract associations of intersectional identities within discourse concerning institutions of power, but restricted its focus on narratives of the nineteenth-century U.S. south. This paper leverages this prior work and introduces an initial study on the association of intersected identities with discourse concerning social institutions within social media from Nigeria. Specifically, we use word embedding models trained on tweets from Nigeria and extract associations of intersected social identities with institutions (e.g., domestic, culture, etc.) to provide insight into the alignment of identities with institutions. Our initial experiments indicate that identities at the intersection of gender and economic status groups have significant associations with discourse about the economic, political, and domestic institutions."
}