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Senda
S
Senda
Developed by larskjeldgaard
This is a BERT model for sentiment polarity analysis ('positive', 'neutral', 'negative') of Danish text.
Downloads 171
Release Time : 3/2/2022
Model Overview
The model is used to detect sentiment polarity in Danish text, trained and tested on tweet data annotated by the Alexandra Institute.
Model Features
Danish Language Specialization
Sentiment analysis model specifically optimized for Danish text
BERT Architecture
Fine-tuned based on the powerful BERT architecture
Three-Class Sentiment Analysis
Capable of identifying 'positive', 'neutral', and 'negative' sentiment polarities
Model Capabilities
Danish text sentiment analysis
Tweet sentiment classification
Use Cases
Social Media Analysis
Tweet Sentiment Monitoring
Analyze the sentiment tendencies of Danish tweets
Identify positive, neutral, or negative emotions in tweets
Customer Feedback Analysis
Product Review Sentiment Analysis
Analyze the sentiment tendencies of Danish customer reviews
Help understand customer satisfaction with products
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