NLP

Lexicon SA VS Machine Learning SA

This project mainly to study sentiment analysis of hotel reviews using two methods which are lexical and machine learning method.

Procedure

This project has been categorized into four parts.

Part I

Using Hotel reviews dataset create lexicon.

Part II

Then use Spacy to do classification. Accuracy is calculated for later use (compare with machine learning method)

Part III

By using Machine learning method (NaiveBayes) to do hotel reviews sentiment analysis. Different algorithms such as Bag of words, TF-IDF and word embedding (Doc2vec) are used.

Part IV

Compare the accuracy Compare the accuracy of both methods (lexical analysis and machine learning). However for this part, more classification method are included to determine the best classifier for hotel reviews dataset. The included classifiers are Logistic Regression, NaiveBayes and SVM.