F

Fear Mongering Detection

Developed by Falconsai
A text classification model based on DistilBERT, specifically designed to detect fear-mongering in text
Downloads 310
Release Time : 11/17/2023

Model Overview

This model effectively identifies fear-inducing content in text by fine-tuning the DistilBERT architecture, suitable for scenarios such as social media monitoring and news analysis

Model Features

High Efficiency
Utilizes the DistilBERT architecture to achieve efficient computation while maintaining high accuracy
Fine-tuned Optimization
Optimized for fear-mongering recognition tasks through 100 epochs of fine-tuning
Semantic Understanding
Capable of capturing subtle semantic nuances and contextual information in natural language

Model Capabilities

Text classification
Fear-mongering recognition
Semantic analysis

Use Cases

Social media monitoring
Fear-mongering detection
Analyze social media posts and comments to identify fear-mongering content
Helps platforms monitor and control content that spreads fear or misinformation
News analysis
News reporting bias analysis
Analyze news reports to identify paragraphs containing fear-inducing language
Assists media organizations and fact-checking groups in evaluating reporting biases
Content moderation
Automated content filtering
Automatically flag or filter content that may be considered fear-mongering
Maintains a positive and healthy online environment
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase