prrao87/fine-grained-sentiment
A comparison and discussion of different NLP methods for 5-class sentiment classification on the SST-5 dataset.
If you work with text data and need to categorize opinions, this project helps you understand how different automated methods perform. It takes raw text like customer reviews or social media posts and classifies them into five sentiment categories (very negative to very positive), showing you the accuracy of various techniques. This is useful for data analysts, market researchers, or anyone needing fine-grained sentiment insights from text.
172 stars. No commits in the last 6 months.
Use this if you need to perform granular sentiment analysis on text and want to compare the effectiveness of multiple classification techniques on your data.
Not ideal if you need a plug-and-play tool for immediate sentiment classification without evaluating different model performances or if you're not comfortable with some technical setup.
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172
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73
Language
Python
License
MIT
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Last pushed
Apr 15, 2025
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