@inproceedings{nandi-etal-2022-detecting,
    title = "Detecting the Role of an Entity in Harmful Memes: Techniques and their Limitations",
    author = "Nandi, Rabindra Nath  and
      Alam, Firoj  and
      Nakov, Preslav",
    editor = "Chakraborty, Tanmoy  and
      Akhtar, Md. Shad  and
      Shu, Kai  and
      Bernard, H. Russell  and
      Liakata, Maria  and
      Nakov, Preslav  and
      Srivastava, Aseem",
    booktitle = "Proceedings of the Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situations",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2022.constraint-1.6/",
    doi = "10.18653/v1/2022.constraint-1.6",
    pages = "43--54",
    abstract = "Harmful or abusive online content has been increasing over time and it has been raising concerns among social media platforms, government agencies, and policymakers. Such harmful or abusive content has a significant negative impact on society such as cyberbullying led to suicides, COVID-19 related rumors led to hundreds of deaths. The content that is posted and shared online can be textual, visual, a combination of both, or a meme. In this paper, we provide our study on detecting the roles of entities in harmful memes, which is part of the CONSTRAINT-2022 shared task. We report the results on the participated system. We further provide a comparative analysis on different experimental settings (i.e., unimodal, multimodal, attention, and augmentation)."
}