JosephAssaker/Twitter-Sentiment-Analysis-Classical-Approach-VS-Deep-Learning
This project's aim, is to explore the world of Natural Language Processing (NLP) by building what is known as a Sentiment Analysis Model. We will be implementing and comparing both a Naïve Bayes and a Deep Learning LSTM model.
This project helps you understand the emotional tone behind social media posts. It takes in raw Twitter data and classifies each tweet as expressing either a positive or negative sentiment. This is useful for market researchers, brand managers, or anyone needing to gauge public opinion from social media.
103 stars. No commits in the last 6 months.
Use this if you want to explore and compare how different methods can automatically sort Twitter content by emotion.
Not ideal if you need a production-ready tool for real-time sentiment analysis or analysis of platforms other than Twitter.
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Dec 04, 2020
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