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Reseach Article

Sentiment Analysis of Tweets for Inferring Popularity of Mobile Phones

by Hema Krishnan, M. Sudheep Elayidom, T. Santhanakrishnan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 157 - Number 2
Year of Publication: 2017
Authors: Hema Krishnan, M. Sudheep Elayidom, T. Santhanakrishnan
10.5120/ijca2017912616

Hema Krishnan, M. Sudheep Elayidom, T. Santhanakrishnan . Sentiment Analysis of Tweets for Inferring Popularity of Mobile Phones. International Journal of Computer Applications. 157, 2 ( Jan 2017), 1-3. DOI=10.5120/ijca2017912616

@article{ 10.5120/ijca2017912616,
author = { Hema Krishnan, M. Sudheep Elayidom, T. Santhanakrishnan },
title = { Sentiment Analysis of Tweets for Inferring Popularity of Mobile Phones },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 157 },
number = { 2 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume157/number2/26800-2016912616/ },
doi = { 10.5120/ijca2017912616 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:49.327499+05:30
%A Hema Krishnan
%A M. Sudheep Elayidom
%A T. Santhanakrishnan
%T Sentiment Analysis of Tweets for Inferring Popularity of Mobile Phones
%J International Journal of Computer Applications
%@ 0975-8887
%V 157
%N 2
%P 1-3
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sentiment analysis is a very popular technique for social network analysis. Sentiment analysis also termed as opinion mining is a process of automatically extracting knowledge from sentiments or opinions of others about some topic or problem. We can identify opinions in a large unstructured/structured data and analyze the polarity of opinions. Twitter is a large and rapidly growing micro blogging social networking website where people express their opinions in a short and simple manner of expressions. It is a common practice that merchants selling products on the Web ask their customers to review the products. In twitter number of customer reviews on different products is appearing. Mobile phones are a common domain in which number of customer reviews appears. This makes it difficult for a potential customer to read them in order to make a decision on whether to buy the product. We are only interested in the specific features of the phones that customers have opinions on and also whether the opinions are positive or negative. This paper presents a lexicon based approach for analyzing the customer reviews on mobile phones over Twitter data to measure the popularity based on which the customer can decide whether to buy the product.

References
  1. T.K. Das, D.P. Acharjya, M.R. Patra, "Opinion Mining about a Product by analysing public tweets in Twitter", IEEE Proceedings of International Conference on Computer Communication and Informatics (ICCI-2014), January 03–05, 2014, Coimbatore, India.
  2. Varsha Sahayak, Vijaya Shete, Apashabi Pathan, "Sentiment Analysis on Twitter Data", International Journal of Innovative Research in Advanced Engineering (IJIRAE) , Issue 1, Volume 2 , January 2015.
  3. Hema Krishnan, M. Sudheep Elayidom, T. Santhanakrishnan, "Impact and Application of Sentiment Analysis using Twitter: A Survey", International J. of Advanced Research in Computer and Communication Engineering, (IJARCCE), Vol. 4, Special Issue 1, 2015, pp. 18–21.
  4. S.M. Vohra, J.B. Teraiyam "A Comparative Sentiment Analysis Technique", Journal Of Information, Knowledge And Research In Computer Engineering, ISSN: 0975 – 6760, Vol. 2, Issue 02, 2013.
  5. https://sites.google.com/site/miningtwitter/questions/sentiment/.
  6. http://www.tutorialspoint.com/mongodb/.
Index Terms

Computer Science
Information Sciences

Keywords

Sentiment opinion score Twitter lexicon