twitter-sentiment-analysis and Twitter-Sentiment-Analysis-Classical-Approach-VS-Deep-Learning
About twitter-sentiment-analysis
abdulfatir/twitter-sentiment-analysis
Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.
This project helps social media analysts, marketers, or researchers understand public opinion by analyzing Twitter data. You provide a CSV file of tweets, some labeled as positive or negative, and it outputs predictions of sentiment for new, unlabeled tweets. It helps you quickly gauge sentiment trends without manual review.
About Twitter-Sentiment-Analysis-Classical-Approach-VS-Deep-Learning
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.
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