Avik-Das-567/Twitter-Sentiment-Analysis-NLP
A Python-based sentiment analysis tool that uses Scikit-Learn and a Naive Bayes classifier to predict tweet sentiment with 95% accuracy.
This tool automatically analyzes thousands of tweets to determine the public's sentiment towards a product or service. You input raw tweet text, and it categorizes each tweet as either positive/neutral or negative. This helps marketers, brand managers, and customer service teams efficiently understand customer feelings without manually reviewing every post.
Use this if you need to quickly process large volumes of Twitter data to gauge overall public opinion or customer satisfaction.
Not ideal if you require highly nuanced sentiment analysis for complex, sarcastic, or culturally specific language, or if false negatives for negative tweets are unacceptable.
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Last pushed
Jan 09, 2026
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