@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/jlcl-multiple-ingestion/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)."
}
Markdown (Informal)
[Detecting the Role of an Entity in Harmful Memes: Techniques and their Limitations](https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.constraint-1.6/) (Nandi et al., CONSTRAINT 2022)
ACL