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Aistockbot
A
Aistockbot
Developed by HanBrar
A pre-trained model based on the RoBERTa architecture, specifically designed for sentiment analysis tasks on Twitter text.
Downloads 23
Release Time : 1/11/2025
Model Overview
This model is a text classification model based on the RoBERTa architecture, fine-tuned for sentiment analysis of Twitter text, capable of identifying positive, negative, or neutral emotions in the text.
Model Features
Twitter Text Optimization
Specially trained and optimized for Twitter text, better handling informal language and unique expressions in tweets.
Efficient Sentiment Analysis
Quickly and accurately identifies sentiment tendencies (positive/negative/neutral) in text.
Based on RoBERTa Architecture
Utilizes the powerful RoBERTa pre-trained model as its foundation, offering excellent text comprehension capabilities.
Model Capabilities
Text Classification
Sentiment Analysis
Social Media Text Processing
Use Cases
Social Media Analysis
Brand Sentiment Monitoring
Analyze sentiment tendencies of user comments about specific brands or products on Twitter.
Accuracy 0.8, F1 score 0.74
Public Opinion Analysis
Monitor emotional reactions to public events or topics on social media.
Market Research
Product Feedback Analysis
Analyze consumer feedback on new product launches via Twitter.
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