@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://aclanthology.org/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).",
}
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%0 Conference Proceedings
%T Detecting the Role of an Entity in Harmful Memes: Techniques and their Limitations
%A Nandi, Rabindra Nath
%A Alam, Firoj
%A Nakov, Preslav
%Y Chakraborty, Tanmoy
%Y Akhtar, Md. Shad
%Y Shu, Kai
%Y Bernard, H. Russell
%Y Liakata, Maria
%Y Nakov, Preslav
%Y Srivastava, Aseem
%S Proceedings of the Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situations
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F nandi-etal-2022-detecting
%X 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).
%R 10.18653/v1/2022.constraint-1.6
%U https://aclanthology.org/2022.constraint-1.6
%U https://doi.org/10.18653/v1/2022.constraint-1.6
%P 43-54
Markdown (Informal)
[Detecting the Role of an Entity in Harmful Memes: Techniques and their Limitations](https://aclanthology.org/2022.constraint-1.6) (Nandi et al., CONSTRAINT 2022)
ACL