@inproceedings{srivastava-vardhan-2020-hcms,
    title = "{HCMS} at {S}em{E}val-2020 Task 9: A Neural Approach to Sentiment Analysis for Code-Mixed Texts",
    author = "Srivastava, Aditya  and
      Vardhan, V. Harsha",
    editor = "Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      May, Jonathan  and
      Shutova, Ekaterina",
    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
    month = dec,
    year = "2020",
    address = "Barcelona (online)",
    publisher = "International Committee for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.semeval-1.167/",
    doi = "10.18653/v1/2020.semeval-1.167",
    pages = "1253--1258",
    abstract = "Problems involving code-mixed language are often plagued by a lack of resources and an absence of materials to perform sophisticated transfer learning with. In this paper we describe our submission to the Sentimix Hindi-English task involving sentiment classification of code-mixed texts, and with an F1 score of 67.1{\%}, we demonstrate that simple convolution and attention may well produce reasonable results."
}