@inproceedings{rajalakshmi-etal-2022-understanding,
    title = "Understanding the role of Emojis for emotion detection in {T}amil",
    author = "Rajalakshmi, Ratnavel  and
      Mattins R, Faerie  and
      Selvaraj, Srivarshan  and
      Shibani, Antonette  and
      Kumar M, Anand  and
      Raja Chakravarthi, Bharathi",
    editor = "Chakravarthi, Bharathi Raja  and
      Murugappan, Abirami  and
      Chinnappa, Dhivya  and
      Hane, Adeep  and
      Kumeresan, Prasanna Kumar  and
      Ponnusamy, Rahul",
    booktitle = "Proceedings of the First Workshop on Multimodal Machine Learning in Low-resource Languages",
    month = dec,
    year = "2022",
    address = "IIIT Delhi, New Delhi, India",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.mmlow-1.2",
    pages = "9--17",
    abstract = "of expressing relevant idea through social media platforms and forums. At the same time, these memes are trolled by a person who tries to get identified from the other internet users like social media users, chat rooms and blogs. The memes contain both textual and visual information. Based on the content of memes, they are trolled in online community. There is no restriction for language usage in online media. The present work focuses on whether memes are trolled or not trolled. The proposed multi modal approach achieved considerably better weighted average F1 score of 0.5437 compared to Unimodal approaches. The other performance metrics like precision, recall, accuracy and macro average have also been studied to observe the proposed system.",
}