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Bert For Japanese Twitter Sentiment
A sentiment analysis model fine-tuned from Japanese Twitter BERT, specifically designed for analyzing sentiment tendencies in Japanese tweets.
Downloads 306
Release Time : 5/13/2024
Model Overview
This model is fine-tuned from Japanese Twitter BERT and is specialized for sentiment classification tasks in Japanese tweets, capable of identifying negative, neutral, and positive sentiments.
Model Features
Specialized for Japanese Twitter
Fine-tuned from Japanese Twitter BERT, optimized specifically for the characteristics of Japanese tweets.
Three-class Sentiment Analysis
Accurately identifies negative, neutral, and positive sentiment tendencies.
High-quality Training Data
Trained using the JTS1k dataset, with mixed sentiment samples removed to improve accuracy.
Model Capabilities
Japanese Text Sentiment Classification
Tweet Sentiment Analysis
Use Cases
Social Media Analysis
Brand Sentiment Monitoring
Analyze user sentiment tendencies regarding specific brands or products on Twitter.
Accurately identifies negative reviews, helping brands respond promptly to PR crises.
Market Research
Collect and analyze immediate consumer feedback on new products or services.
Provides quantified sentiment distribution data to assist in market decision-making.
Customer Service
Customer Feedback Analysis
Automatically classify sentiment tendencies in customer tweets.
Prioritizes negative feedback to improve customer satisfaction.
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