Sentiment Analysis Using Machine Learning Approach

Sentiment Analysis Using Machine Learning Approach

Blog Article

Customers feedback is a valuable asset for businesses, that can be used in order to improve their performance.One of the fastest spreading areas today Style in computer science - Sentiment Analysis, helps to extract precious information from textual data, in order to identify the feeling of a statement.This research aims to build a classifier to predict customers’ satisfaction, based on Amazon reviews dataset, for different brands of mobile phones.

The paper proposes a comparison between four text classification algorithms - PANTOTHENIC ACID Naïve Bayes, Support Vector Machine, Decision Tree and Random Forest, using different feature extraction techniques, such as Bag of words and TF-IDF.In addition, the models are evaluated using accuracy, precision, recall and F-score metrics.Our experiments revealed that Support Vector Machine achieves the best results and is very suitable for classification of the sentiment on product reviews.