CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Sentiment Analysis of Movie Reviews using Machine Learning Techniques

by Palak Baid, Apoorva Gupta, Neelam Chaplot
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 7
Year of Publication: 2017
Authors: Palak Baid, Apoorva Gupta, Neelam Chaplot
10.5120/ijca2017916005

Palak Baid, Apoorva Gupta, Neelam Chaplot . Sentiment Analysis of Movie Reviews using Machine Learning Techniques. International Journal of Computer Applications. 179, 7 ( Dec 2017), 45-49. DOI=10.5120/ijca2017916005

@article{ 10.5120/ijca2017916005,
author = { Palak Baid, Apoorva Gupta, Neelam Chaplot },
title = { Sentiment Analysis of Movie Reviews using Machine Learning Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2017 },
volume = { 179 },
number = { 7 },
month = { Dec },
year = { 2017 },
issn = { 0975-8887 },
pages = { 45-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number7/28752-2017916005/ },
doi = { 10.5120/ijca2017916005 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:54:45.417729+05:30
%A Palak Baid
%A Apoorva Gupta
%A Neelam Chaplot
%T Sentiment Analysis of Movie Reviews using Machine Learning Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 7
%P 45-49
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sentiment analysis is the analysis of emotions and opinions from any form of text. Sentiment analysis is also termed as opinion mining. Sentiment analysis of the data is very useful to express the opinion of the mass or group or any individual. This technique is used to find the sentiment of the person with respect to a given source of content. Social media and other online platforms contain a huge amount of the data in the form of tweets, blogs, and updates on the status, posts, etc. In this paper, we have analyzed the Movie reviews using various techniques like Naïve Bayes, K-Nearest Neighbour and Random Forest.

References
  1. Joscha Markle-Huß, Stefan Feuerriegel, Helmut Prendinger. 2017 Improving Sentiment Analysis with Document-Level Semantic Relationships from Rhetoric Discourse Structures, Proceedings of the 50th Hawaii International Conference on System Sciences.
  2. A. Hogenboom, F. Frasincar, F. de Jong, and U. Kaymak,. 2015, Using Rhetorical Structure in Sentiment Analysis, Communications of the ACM, vol. 58, no. 7, pp. 69–77.
  3. Amir Hossein Yazdavar, MonirehEbrahimi, Naomie Salim, 2016, Fuzzy Based Implicit Sentiment Analysis on Quantitative Sentences, Faculty of Computing, UniversitiTechnologi Malaysia, Johor, Malaysia, Journal of Soft Computing and Decision Support Systems vol 3:4, pp.7-18.
  4. Bhatia, R. S., Graystone, A., Davies, R. A., McClinton, S., Morin, J., & Davies, R. F. 2010, Extracting information for generating a diabetes report card from free text in physicians notes. Paper presented at the Proceedings of the NAACL HLT 2010 Second Louhi Workshop on Text and Data Mining of Health Documents.
  5. Dhiraj Murthy, Twitter and elections: are tweets, predictive, reactive, or a form of buzz?, Information, Communication & Society, 18:7, 816-831, DOI:10.1080/1369118X.2015.1006659
  6. Kamal A., 2015, Review Mining for Feature Based Opinion Summarization and Visualization.
  7. Kamal, A. 2013 Subjectivity Classification using Machine Learning Techniques for Mining Feature- Opinion Pairs from Web Opinion Sources. International Journal of Computer Science Issues 10(5), 191- 200.
  8. Humera Shaziya, G.Kavitha, Raniah Zaheer, 2015, Text Categorization of Movie Reviews for Sentiment Analysis , International Journal of Innovative Research in Science, Engineering and Technology, Vol. 4, Issue11.
  9. Akshay Amolik, Niketan Jivane, Mahavir Bhandari, Dr .M. Venkatesan, Twitter Sentiment Analysis of Movie Reviews using Machine Learning Techniques, School of Computer Science and Engineering, VIT University, Vellore.
  10. Y. Wu and F. Ren, 2011, Learning Sentimental influence in twitter, Future Computer Science and Application (ICFCSA), 2011, International Conference IEEE vol. 119122.
Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Opinion Mining Movies Reviews Naive Bayes K-Nearest Neighbour Random Forest.

Powered by PhDFocusTM