A Big Data-empowered System for Real-time Detection of Regional Discriminatory Comments on Vietnamese Social Media
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Abstract (arXiv)
Regional discrimination is a persistent social issue in Vietnam. While existing research has explored hate speech in the Vietnamese language, the specific issue of regional discrimination remains under-addressed. Previous studies primarily focused on model development without considering practical system implementation. In this work, we propose a task called Detection of Regional Discriminatory Comments on Vietnamese Social Media, leveraging the power of machine learning and transfer learning models. We have built the ViRDC (Vietnamese Regional Discrimination Comments) dataset, which contains comments from social media platforms, providing a valuable resource for further research and development. Our approach integrates streaming capabilities to process real-time data from social media networks, ensuring the system's scalability and responsiveness. We developed the system on the Apache Spark framework to efficiently handle increasing data inputs during streaming. Our system offers a comprehensive solution for the real-time detection of regional discrimination in Vietnam.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 10 references that are in the map. First posted on arXiv 29 Oct 2024.
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References · 6
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
- 2020PhoBERT: Pre-trained language models for Vietnamesecited by 148
- 2021A Large-scale Dataset for Hate Speech Detection on Vietnamese Social Media Textscited by 25
- 2022Vietnamese Hate and Offensive Detection using PhoBERT-CNN and Social Media Streaming Datacited by 9
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