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

arXiv: https://arxiv.org/abs/2411.06138 · HTML: https://mlsanity.com/paper/2411.06138/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Safety alignment, refusal and guardrails, one of 12 directions in LLM safety and security.
- Builds on 14 of its 36 references that are in the map.
- First posted on arXiv 9 Nov 2024.

## Placed in

- LLM safety and security / [Safety alignment, refusal and guardrails](https://mlsanity.com/safety/safety-alignment-refusal-and-guardrails/)

## Builds on (most cited first, 14 of 14)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [node2vec: Scalable Feature Learning for Networks](https://mlsanity.com/paper/1607.00653/) (2016)
- [Automated Hate Speech Detection and the Problem of Offensive Language](https://mlsanity.com/paper/1703.04009/) (2017)
- [Deep Learning for Hate Speech Detection in Tweets](https://mlsanity.com/paper/1706.00188/) (2017)
- [Challenges for Toxic Comment Classification: An In-Depth Error Analysis](https://mlsanity.com/paper/1809.07572/) (2018)
- [EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture](https://mlsanity.com/paper/2301.12805/) (2023)
- [It's All in the Embedding! Fake News Detection Using Document Embeddings](https://mlsanity.com/paper/2304.07781/) (2023)
- [DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News Detection](https://mlsanity.com/paper/2302.01756/) (2023)
- [MCWDST: a Minimum-Cost Weighted Directed Spanning Tree Algorithm for Real-Time Fake News Mitigation in Social Media](https://mlsanity.com/paper/2302.12190/) (2023)
- [MisRoBAERTa: Transformers versus Misinformation](https://mlsanity.com/paper/2304.07759/) (2023)
- [A Scalable Document-based Architecture for Text Analysis](https://mlsanity.com/paper/1612.06195/) (2016)
- [CONTAIN: A Community-based Algorithm for Network Immunization](https://mlsanity.com/paper/2303.01934/) (2023)

## Built on by (most cited first, 2 of 2)

- [MatchLM2Lite: A Scalable MLLM-to-Lite Framework for Reproduced Content Identification](https://mlsanity.com/paper/2606.14786/) (2026)
- [GETAE: Graph information Enhanced deep neural NeTwork ensemble ArchitecturE for fake news detection](https://mlsanity.com/paper/2412.01825/) (2024)

## Abstract (arXiv)

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 textscStopHC, a harmful content detection and mitigation architecture for social media platforms. Our aim with textscStopHC 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.