UM Research Repository
metadata only
Code-mixing unveiled: Enhancing the hate speech detection in Arabic dialect tweets using machine learning models
Technological developments over the past few decades have changed the way people communicate, with platforms like social media and blogs becoming vital channels for international conversation. Even though hate speech is vigorously suppressed on social media, it is still a concern that needs to be co
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Sentiment analysis for hate speech detection on social media: TF-IDF weighted N-Grams based approach#956873
- Use of regular expressions for multilingual detection of Hate speech in Kenya#957199
- AIWizards at MULTIPRIDE: A Hierarchical Approach to Slur Reclamation Detection#1105950
- Sledgehammer or Scalpel? A Fine-grained Adaptive Framework for Implicit Hate Speech#780781
- Sledgehammer or Scalpel? A Fine-grained Adaptive Framework for Implicit Hate Speech#779406
Record · ID 1318085
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive