International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 8, No. 8, 8 Aug. 2016
Cover page and Table of Contents: PDF (size: 415KB)
Sentiment Analysis on Movie Reviews: A Comparative Study of Machine Learning Algorithms and Open Source Technologies
Full Text (PDF, 415KB), PP.66-70
Views: 0 Downloads: 0
Author(s)
B. Narendra
1,*
K. Uday Sai
1
G. Rajesh
1
K. Hemanth
1
M. V. Chaitanya Teja
1
K. Deva Kumar
1
Index Terms
Sentiment Analysis, Machine Learning, Naïve Bayes Algorithm, Apache Hadoop, Map Reduce paradigm
Abstract
Social Networks such as Facebook, Twitter, Linked In etc… are rich in opinion data and thus Sentiment Analysis has gained a great attention due to the abundance of this ever growing opinion data. In this research paper our target set is movie reviews. There are diverge range of mechanisms to express their data which may be either subjective, objective or a mixture of both. Besides the data collected from World Wide Web consists of lot of noisy data. It is very much true that we are going to apply some pre-processing techniques and compare the accuracy using Machine Learning algorithm Naïve Bayes Classifier. With ever growing demand to mine the Big Data the open source software technologies such as Hadoop using map reducing paradigm has gained a lot of pragmatic importance. This paper illustrates a comparitive study of sentiment analysis of movie reviews using Naïve Bayes Classifier and Apache Hadoop in order to calculate the performance of the algorithms and show that Map Reduce paradigm of Apache Hadoop performed better than Naïve Bayes Classifier.
Cite This Paper
B. Narendra, K. Uday Sai, G. Rajesh, K. Hemanth, M. V. Chaitanya Teja, K. Deva Kumar, "Sentiment Analysis on Movie Reviews: A Comparative Study of Machine Learning Algorithms and Open Source Technologies", International Journal of Intelligent Systems and Applications (IJISA), Vol.8, No.8, pp.66-70, 2016. DOI:10.5815/ijisa.2016.08.08
Reference
[1]Christos Troussas, Maria Virvou, Kurt Junshean Espinosa, Kevin Llaguno, Jaime Caro, ”Sentiment Analysis of Facebook statuses using Naïve Bayes classifier for language learning”, Proceedings ofInformation, Intelligence, Systems and Applications (IISA), 2013 Fourth International Conference on 10-12 july 2013
[2]Charit Pong-inwong, Wararat Songpan ,”TeachingSenti-Lexicon for Automated Sentiment Polarity Definition in Teaching Evaluation”, Proceedings of Semantics, Knowledge and Grids (SKG), 2014 10th International Conference on 27-29 August 2014.
[3]Jalel Akaichi, ”Social Networks ‘ Facebook’ Statuses Updates Mining for Sentiment Classification”, proceedings of SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013
[4]Na Fan, Wandong Cai, Yu Zhao,“Research on the Model of Multiple Levels for Determining Sentiment of Text”, Proceedings of 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application.
[5]Vipin Kumar, Sonajharia Minz,”Mood Classification of Lyrics using SentiWordNet” ,Proceedings of 2013 International Conference on Computer Communication and Informatics(ICCCI-2013), Jan. 04-06, 2013, Coimbatore, INDIA
[6]Rawan T. Khasawneh, Heider A. Wahsheh, Mohammed N. Al-Kabi, Izzat M. Alsmadi, “Sentiment Analysis of Arabic Social Media Content: A Comparative Study, 2013”, Proceedings of the 8th International Conference for Internet Technology and Secured Transactions(ICITST-2013)
[7]Jalel Akaichi, zeineb Dhouioui, Maria Jose Lopez-Huertas Perez,“Text Mining Facebook Status Updates for Sentiment Classification, 2013”, Proceedings of System Theory, Control and Computing(ICSTCC), 2013 17th International Conference
[8]Addlight Mukwazvure, K.P Supreethi,“A Hybrid Approach to Sentiment Analysis of News Comments, 2015” ,Reliability, Infocom Technologies and Optimization(ICRITO), 2-4 Sept. 2015.
[9]K. Mouthami, K. Nirmala Devi, V. Murali Bhaskaran,” Sentiment Analysis and Classification Based On Textual Reviews, 2014”, Proceedings of Information Communication and Embedded Systems (ICICIES), 21-23 Feb 2013.
[10]Sudipto Shankar Dasgupta, Swaminathan Natarajan, Kiran Kumar Kaipa, Sujay Kumar Bhattacherjee, Arun Viswanathan,“Sentiment Analysis of Facebook Data using Hadoop based Open Source Technologies, 2015” Proceedings of Data Science and Advanced Analytics(DSAA),2015 19-21Oct.2015.
[11]Gaurav D Rajurkar, Rajeshwari M Goudar, ”A speedy data uploading approach for Twitter Trend And Sentiment Analysis using Hadoop”, Proceedings 2015 International Conference on Computing Communication Control and Automation.
[12]Mykhailo Lobur, AnDriy Romanyuk, Mariana Romanyshyn, ”Using NLTK for educational and scientific purposes”, Proceedings of CAD Systems in Microelectronics(CADSM), 2011 11th International Conference.
[13]http://www.nltk.org/book/ch02.html
[14]http://www.nltk.org/api/nltk.html
[15]http://www.nltk.org/book/ch01.html
[16]Shankar Gznesh Manikandan, Siddharth Ravi, “Big Data Analysis Using Apache Hadoop”, Proceedings of IT Convergence and Security (ICITCS), 2014 International Conference on 28-30 Oct. 2014
[17]Milind Bhandarkar, “MapReduce Programming with apache Hadoop” ,Proceedings of Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on 19-23 April 2010.
[18]https://pig.apache.org/docs/r0.7.0/tutorial.html
[19]http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/
[20]P. Dhana Lakshmi, K. Ramani, B. Eswara Reddy, “Feature Relevance Analysis in Online Marketing To Improve Productivity”, proceedings journal of Software Engineering, Volume 9.No.3, jan-mar 15, ISSNO 973-5151.