@inproceedings{sarkar-etal-2020-non,
    title = "The Non-native Speaker Aspect: {I}ndian {E}nglish in Social Media",
    author = "Sarkar, Rupak  and
      Mahinder, Sayantan  and
      KhudaBukhsh, Ashiqur",
    editor = "Xu, Wei  and
      Ritter, Alan  and
      Baldwin, Tim  and
      Rahimi, Afshin",
    booktitle = "Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/2020.wnut-1.9/",
    doi = "10.18653/v1/2020.wnut-1.9",
    pages = "61--70",
    abstract = "As the largest institutionalized second language variety of English, Indian English has received a sustained focus from linguists for decades. However, to the best of our knowledge, no prior study has contrasted web-expressions of Indian English in noisy social media with English generated by a social media user base that are predominantly native speakers. In this paper, we address this gap in the literature through conducting a comprehensive analysis considering multiple structural and semantic aspects. In addition, we propose a novel application of language models to perform automatic linguistic quality assessment."
}