Sweta Tiwari

Work place: Department of Computer Science & Engineering, Heritage Institute of Technology, Kolkata, India

E-mail: sweta.tiwari604@gmail.com


Research Interests: Pattern Recognition, Data Mining, Data Compression, Data Structures and Algorithms


Sweta Tiwari: She has completed her B-Tech from Heritage Institute of Technology on Computer Science & Engineering. Her areas of interest are data mining, pattern classification.

Author Articles
Sentiment Analysis of Review Datasets Using Naïve Bayes‘ and K-NN Classifier

By Lopamudra Dey Sanjay Chakraborty Anuraag Biswas Beepa Bose Sweta Tiwari

DOI: https://doi.org/10.5815/ijieeb.2016.04.07, Pub. Date: 8 Jul. 2016

The advent of Web 2.0 has led to an increase in the amount of sentimental content available in the Web. Such content is often found in social media web sites in the form of movie or product reviews, user comments, testimonials, messages in discussion forums etc. Timely discovery of the sentimental or opinionated web content has a number of advantages, the most important of all being monetization. Understanding of the sentiments of human masses towards different entities and products enables better services for contextual advertisements, recommendation systems and analysis of market trends. The focus of our project is sentiment focussed web crawling framework to facilitate the quick discovery of sentimental contents of movie reviews and hotel reviews and analysis of the same. We use statistical methods to capture elements of subjective style and the sentence polarity. The paper elaborately discusses two supervised machine learning algorithms: K-Nearest Neighbour(K-NN) and Naïve Bayes‘ and compares their overall accuracy, precisions as well as recall values. It was seen that in case of movie reviews Naïve Bayes‘ gave far better results than K-NN but for hotel reviews these algorithms gave lesser, almost same accuracies.

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