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Language: Jupyter Notebook Python 3
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Dataset link: https://www.kaggle.com/c/restaurant-reviews The dataset is Yelp Reviews from different shops, like restaurants, retailers and body shops. I select the first 1000 lines and each line contains a star rating (1,2,3,4 or 5) and a text review.
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What it does?
The goal is to perform Sentiment Analysis from the text review only. And it is conducted with 2 methods.
The first one is extracting opinion segments and computing polarity score. Segments are classified based on whether the polarity score is positive or negative. (NLP)
The second one is using machine learning methodologies-Logistic Regression, Decision Tree, Random Forest and KNN. (Text Mining)
To further my research, I also perform topic modeling to get an idea of the topics covered in reviews.
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Text Mining using machine learning methodologies & some NLP opinion extraction
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