Sentiment Classification using Machine Learning Techniques
Journal: International Journal of Science and Research (IJSR) (Vol.5, No. 4)Publication Date: 2016-04-05
Authors : Suchita V Wawre; Sachin N Deshmukh;
Page : 819-821
Keywords : Sentimental Analysis; supervised Algorithm; Naive bayes; Support vector machine;
Abstract
Large amount of information are available online on web. The discussion forum, review sites, blogs are some of the opinion rich resources where review or posted articles is their sentiment, or overall opinion towards the subject matter. The opinions obtained from those can be classified in to positive or negative which can be used by customer to make product choice and by businessmen for finding customer satisfaction. This paper studies online movie reviews using sentiment analysis approaches. In this study, sentiment classification techniques were applied to movie reviews. Specifically, we compared two supervised machine learning approaches SVM, Navie Bayes for Sentiment Classification of Reviews. Results states that Nave Bayes approach outperformed the svm. If the training dataset had a large number of reviews, Naive bayes approach reached high accuracies as compare to other.
Other Latest Articles
- A Survey of Protocols Enhancing the Security and Performance of AODV
- The Role of Agricultural Extension Media to Increase Knowledge of Corn Farmers in Tidore Islands District of North Maluku, Indonesia
- Sonographic Measurement of Fetal Kidney Length as Parameter for Fetal Weight Estimation for Sudanese Population
- Comparison of Anthropometric and Body Composition Characteristics in Children and Adolescents of Asian Indian Origin: Santiniketan Maturity Study
- Larvicidal and Antagonistic Activities of Crude Leaf Extracts of Pyrethrum (Chrisanthemam: Compositae), Eucalyptus camaldulensis Sm. Myrtaceae, and Nicotiana tabaccum (Tobacco L.) (Solanaceae) Against Third Instar Larvae of the Malaria Vector, Anopheles g
Last modified: 2021-07-01 14:33:56