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Hate Speech Detector
This model is a branch version based on the bert-based-uncased-hatespeech-movies model, used to classify text as normal, offensive, or hate speech.
Downloads 16
Release Time : 3/2/2022
Model Overview
This model is a text classification model specifically designed to detect hate speech, offensive language, and normal text in social media and movie subtitles.
Model Features
Multi-category Classification
Capable of classifying text into three categories: normal, offensive, or hate speech.
Social Media Optimization
The model was trained on Twitter comments, making it suitable for analyzing social media contexts.
Movie Subtitle Adaptation
Fine-tuned using movie subtitle datasets, enhancing performance in film and TV content.
Model Capabilities
Text Classification
Hate Speech Detection
Offensive Language Identification
Use Cases
Content Moderation
Social Media Comment Moderation
Automatically identify and filter hate speech and offensive content on social media platforms.
Improve community environment quality and reduce the spread of harmful content.
Film and TV Content Analysis
Analyze the linguistic tendencies in movie and TV show subtitles.
Help content creators and platforms understand the linguistic characteristics of their works.
Academic Research
Language Behavior Research
Used to study language usage patterns and trends in online and film/TV content.
Provide data support for sociology and linguistics research.
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