@inproceedings{kanta-sidorov-2023-selam,
    title = "Selam@{D}ravidian{L}ang{T}ech:Sentiment Analysis of Code-Mixed {D}ravidian Texts using {SVM} Classification",
    author = "Kanta, Selam  and
      Sidorov, Grigori",
    editor = "Chakravarthi, Bharathi R.  and
      Priyadharshini, Ruba  and
      M, Anand Kumar  and
      Thavareesan, Sajeetha  and
      Sherly, Elizabeth",
    booktitle = "Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages",
    month = sep,
    year = "2023",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.dravidianlangtech-1.24/",
    pages = "176--179",
    abstract = "Sentiment analysis in code-mixed text written in Dravidian languages. Specifically, Tamil- English and Tulu-English. This paper describes the system paper of the RANLP-2023 shared task. The goal of this shared task is to develop systems that accurately classify the sentiment polarity of code-mixed comments and posts. be provided with development, training, and test data sets containing code-mixed text in Tamil- English and Tulu-English. The task involves message-level polarity classification, to classify YouTube comments into positive, negative, neutral, or mixed emotions. This Code- Mix was compiled by RANLP-2023 organizers from posts on social media. We use classification techniques SVM and achieve an F1 score of 0.147 for Tamil-English and 0.518 for Tulu- English."
}