Document Level Sentiment Analysis for Product Review using Dictionary Based Approach
| International Journal of Computer Science and Engineering |
| © 2017 by SSRG - IJCSE Journal |
| Volume 4 Issue 6 |
| Year of Publication : 2017 |
| Authors : Paramita Ray |
10.14445/23488387/IJCSE-V4I6P105
How to Cite?
Paramita Ray, "Document Level Sentiment Analysis for Product Review using Dictionary Based Approach," SSRG International Journal of Computer Science and Engineering , vol. 4, no. 6, pp. 24-29, 2017. Crossref, https://doi.org/10.14445/23488387/IJCSE-V4I6P105
Abstract:
In recent times, people share their opinions, ideas through social networking site, electronic media etc. Different organizations always want to find public opinions about their products and services. Individual consumers also want to know the opinions from existing users before purchasing product. Sentiment analysis is the computational treatment of user’s opinions, sentiments and subjectivity of text. In this paper we propose a framework for sentiment analysis using R software which can analyze sentiment of users on Twitter data using Twitter API. Our methodology involves collection of data from twitter, its preprocessing and followed by a lexicon based approach to analyze user’s sentiment.
Keywords:
Twitter, Sentiment Analysis, Lexical Analysis.
References:
[1] Olga Kolchyna1, Th´arsis T. P. Souza1, Philip C. Treleaven12 and Tomaso AsteTwitter Sentiment Analysis: Lexicon Method, Machine Learning Method and Their Combination , Department of Computer Science, UCL, Gower Street, London,
[2] Bing Liu, Sentiment Analysis and Opinion Mining April 22, 2012
[3] Suvendra Kumar Jayasingh, Jibendu Kumar Mantri, P. Gahan Comparison between J48 Decision Tree, SVM and MLP in Weather Forecasting 10.14445/23488387/IJCSEV3I11P109
[4] Harsh Thakkar and Dhiren Patel, Approaches for Sentiment Analysis on Twitter: A State-of-Art study , Department of Computer Engineering, NIT, Surat- 395007, India.
[5] Apoorv Agarwal Boyi Xie Ilia Vovsha Owen Rambow Rebecca Passonneau,, Sentiment Analysis of Twitter Data , Department of Computer Science ,Columbia University.New York, NY 10027 USA
[6] Cataldo Musto, Giovanni Semeraro, Marco Polignano, A comparison of Lexicon-based approachesfor Sentiment Analysis of microblog Department of Computer Science, University of Bari Aldo Moro, Italy
[7] James Spencer and Gulden Uchyigit,Sentimentor: Sentiment Analysis of Twitter Data.School of Computing, Engineering and Mathematics.University of Brighton
[8] Anna Jurek,Maurice D. Mulvenna and Yaxin Bi,Improved lexicon-based sentiment analysis for social media analyticsScience direct,Published: 9 December 2015
[9] Dr.E.Kesavulu Reddy .14445/23488387/IJCSEV3I11P107
[10] http://en.wikipedia.org/wiki/List_of_emoticons.
[11] http://www.acronymfinder.com/
[12] Akshi Kumar and Teeja Mary Sebastian, Sentiment Analysis on Twitter, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 3, July 2012,Dept of Computer Engineering, Delhi Technological University Delhi, India