short-paper

OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst

Authors:

Kam-Fai WongAuthors Info & Claims

WWW '24: Companion Proceedings of the ACM Web Conference 2024

Pages 1892 - 1895

https://doi.org/10.1145/3589335.3665995

Published: 24 July 2024 Publication History

Abstract

Memes, typically comprising an image with corresponding text, spread personal opinions and positions rapidly across the internet. However, this same characteristic makes them a powerful tool for disseminating social bias and prejudice. Such harmful memes can perpetuate stereotypes, foster discrimination, and exacerbate social divisions in a wide variety of social dimensions, including race, religion, sexual orientation, and more. Recognizing this issue, AI Singapore has launched the Online Safety Prize Challenge to stimulate research of technologies that can effectively detect harmful memes, particularly in Singapore's multicultural and multilingual context. Given the country's linguistic diversity, these memes could be created and spread in various languages, including English, Chinese, Malay, and Tamil. This adds an additional layer of complexity to the detection process, as the memes not only embody the multimodal nature combining visual imagery with text to convey messages that are often nuanced and context-dependent but also do so across different cultural and linguistic contexts.

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Cited By

Lim YHee MYee XYau WSim XTay WNg WNg SLee RChua TNgo CKumar RLauw HKa-Wei Lee R(2024)AISG's Online Safety Prize Challenge: Detecting Harmful Social Bias in Multimodal MemesCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3665993(1884-1891)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3665993

Index Terms

OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
    2. Natural language processing
      1. Machine translation
  2. Machine learning
2. Information systems
  1. World Wide Web

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Published In

cover image ACM Conferences

WWW '24: Companion Proceedings of the ACM Web Conference 2024

May 2024

1928 pages

ISBN:9798400701726

DOI:10.1145/3589335

General Chairs:
Tat-Seng Chua
National University of Singapore
,
Chong-Wah Ngo
Singapore Management University
,
Program Chairs:
Ravi Kumar
Google
,
Hady W. Lauw
Singapore Management University
,
Roy Ka-Wei Lee
Singapore University of Technology and Design

Copyright © 2024 ACM.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 July 2024

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WWW '24

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WWW '24: The ACM Web Conference 2024

May 13 - 17, 2024

Singapore, Singapore

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Cited By

Lim YHee MYee XYau WSim XTay WNg WNg SLee RChua TNgo CKumar RLauw HKa-Wei Lee R(2024)AISG's Online Safety Prize Challenge: Detecting Harmful Social Bias in Multimodal MemesCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3665993(1884-1891)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3665993

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