mlsanityData to 7 Oct 2026

Towards A Multi-agent System for Online Hate Speech Detection

arXiv 2105.01129 ↗First posted 3 May 2021cs.AI cs.CL cs.CVcited by 2

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Abstract (arXiv)

This paper envisions a multi-agent system for detecting the presence of hate speech in online social media platforms such as Twitter and Facebook. We introduce a novel framework employing deep learning techniques to coordinate the channels of textual and im-age processing. Our experimental results aim to demonstrate the effectiveness of our methods for classifying online content, training the proposed neural network model to effectively detect hateful instances in the input. We conclude with a discussion of how our system may be of use to provide recommendations to users who are managing online social networks, showcasing the immense potential of intelligent multi-agent systems towards delivering social good.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 37 of its 59 references that are in the map. First posted on arXiv 3 May 2021.

Builds on

37 of 59 references.

References · 37

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25 more
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Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2023Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Mediacited by 6
  2. 2024MHS-STMA: Multimodal Hate Speech Detection via Scalable Transformer-Based Multilevel Attention Frameworkcited by 2