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arXiv · 2411.06138

StopHC: A Harmful Content Detection and Mitigation Architecture for Social Media Platforms

Ciprian-Octavian Truică·Ana-Teodora Constantinescu·Elena-Simona Apostol
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Abstract

The mental health of social media users has started more and more to be put at risk by harmful, hateful, and offensive content. In this paper, we propose \textsc{StopHC}, a harmful content detection and mitigation architecture for social media platforms. Our aim with \textsc{StopHC} is to create more secure online environments. Our solution contains two modules, one that employs deep neural network architecture for harmful content detection, and one that uses a network immunization algorithm to block toxic nodes and stop the spread of harmful content. The efficacy of our solution is demonstrated by experiments conducted on two real-world datasets.

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Ciprian-Octavian Truică, Ana-Teodora Constantinescu, Elena-Simona Apostol. 2024-11-09. StopHC: A Harmful Content Detection and Mitigation Architecture for Social Media Platforms. https://arxiv.org/abs/2411.06138

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