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Autonlp Tweet Sentiment Extraction 20114061
A
Autonlp Tweet Sentiment Extraction 20114061
Developed by amansolanki
This is a multi-class classification model trained using AutoNLP, specifically designed for tweet sentiment analysis.
Downloads 453
Release Time : 3/2/2022
Model Overview
The model is trained using the AutoNLP framework, focusing on extracting sentiment information from tweets, suitable for sentiment classification tasks in social media content.
Model Features
Efficient Sentiment Analysis
Optimized specifically for tweet content, capable of accurately identifying multiple sentiment categories.
Low Resource Consumption
The training process produces only 3.65 grams of CO2 emissions, environmentally friendly.
Ready-to-use API
Provides simple REST API and Python interfaces for quick integration.
Model Capabilities
Text Classification
Sentiment Analysis
Social Media Content Analysis
Use Cases
Social Media Analysis
Brand Sentiment Monitoring
Analyze the sentiment tendencies of users' tweets about brands or products.
Accuracy around 80%, effectively identifies positive, negative, and neutral reviews.
Market Research
Collect and analyze public emotional reactions to specific topics.
Macro F1 score reaches 0.807, reliably distinguishes subtle emotional differences.
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