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Multi-Label Extremism and Jihadism Classification Tweets Dataset
- Citation Author(s):
-
Mahamodul HasanMahadi
Md. NasifSafwan - Submitted by:
- Mahamodul Hasan...
- Last updated:
- Fri, 08/30/2024 - 08:47
- DOI:
- 10.21227/6gmh-1b80
- Data Format:
- License:
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Abstract
The "Multi-Label Extremism and Jihadism Classification Tweets Dataset" dataset is a multilingual resource designed for multi-label classification of online extremism and toxic behavior, including extremism and jihadism. Each comment is annotated with labels indicating the presence of various extremism traits: toxic, severe toxic, obscenity, threats, insults, identity hate, and jihadi content. This dataset is valuable for research in automated content moderation, enabling the detection of harmful and extremist content across multiple languages, and contributing to the development of safer online environments by providing a diverse array of real-world examples.
Comments
The "Terrorism and Multi-Toxic Labels Classification" dataset is a multilingual dataset curated to assist in the development and evaluation of models aimed at detecting online extremism and toxic behaviors. This dataset is particularly suited for tasks involving multi-label classification, where each comment may exhibit multiple forms of extremism and toxicity.