The intensification of Technology has altered the means of people’s communication by means of opinions, views, sentiments and emotions regarding particular product, services, and people on social networking sites .Social Networking sites are defined as a network of reaction, interaction and relations. Many Social Networking sites, like facebook, whatsapp, Twitter, LinkedIn, Google+, YouTube, Pinterest, Instagram, and Tumblr are the medium to convey the user emotions in form of comments for particular topic. But day by day as huge amount of data is generated from these sites. It becomes a challenging task to perform such type of analysis on big data. R is used to perform the analysis of tweets data that are having a size in GBs. Sentiment analysis, subjectivity analysis and opinion mining are the various techniques to process the review .This paper presented an approach to analyze and visualize twitter data with R. Mainly four types of attitudes are connected with each text positive, negative, neutral and uninterested. Each tweet is analyzed for detecting the sentiments attached to it.

Twitter, Data Analysis, Sentiments, Social Media, Emotion Analysis

[1] R. Parikh and M. Movassate, “Sentiment Analysis of User- Generated Twitter Updates using Various Classification Techniques", CS224N Final Report, pp. 1-18, 2009
[2] Go, R. Bhayani, L.Huang, “Twitter Sentiment Classification Using Distant Supervision”., Stanford University, Technical Paper,2009
[3] A.Pak and P. Paroubek, "Twitter as a Corpus for Sentiment Analysis and Opinion Mining", In Proceedings of the Seventh Conference on International Language Resources and Evaluation, pp.1320-1326,2010.
[4] Bifet and E. Frank, "Sentiment Knowledge Discovery in Twitter Streaming Data", In Proceedings of the 13th International Conference on Discovery Science, Berlin, Germany: Springer, pp. 1-15,2010.
[5] Agarwal, B. Xie, I. Vovsha, O. Rambow, R. Passonneau, “Sentiment Analysis of Twitter Data", In Proceedings of the ACL 2011Workshop on Languages in Social Media, pp. 30-38, 2011.
[6] Po-Wei Liang, Bi-Ru Dai, “Opinion Mining on Social Media Data", IEEE 14th International Conference on Mobile Data Management, Milan, Italy, June 3 - 6, 2013, pp 91-96, 2013.
[7] Vishal A. Kharde, S.S. Sonawane, "Sentiment Analysis of Twitter Data: A Survey of Techniques". International Journal of Computer Applications, Volume 139 – No.11, pp. 5-15, April 2016.
[8] Jahiruddin, "Sentiment Analysis of Twitter Data using Statistical Methods", International Journal of Innovative Research in Engineering & Management (IJIREM), Volume-2, Issue-4, pp. 30-34, July 2015.
[9] Hana Anber, Akram Salah, A. A. Abd El-Aziz3. "A Literature Review on Twitter Data Analysis", International Journal of Computer and Electrical Engineering. Volume 8, Number 3, pp. 241-249, June 2016.
[10] I.Hemalatha, G. P Saradhi Varma, Dr. A. Govardhan. "Preprocessing the Informal Text for efficient Sentiment Analysis", International Journal of Emerging Trends & Technology in Computer Science (IJETTCS). Volume 1, Issue 2, pp.58-61, July – August 2012.
[11] Adam Crymble, "An Analysis of Twitter and Facebook use by the Archival Community" in Archivaria 70, pp. 125-151, 2010.
[12] Chetashri Bhadane, Hardi Dalal and Heenal Doshi, ”Sentiment Analysis-Measuring Opinions”, International Conference on Advanced Computing Technologies and Applications (ICACTA), vol. 45, pp. 808–814, 2015.
[13] Xing Fang and Justin Zhan, “Sentiment Analysis Using Product Review Data”, Journal of Big Data, pp. 1-14, Springer, 2015.
[14] Xia Hu, Jiliang Tang, Huiji Gao and Huan, Liu, ” Unsupervised Sentiment Analysis with Emotional Signals”, Proceedings of the 22nd International Conference on World Wide Web, WWW’13, ACM, pp. 607-617,2013.
[15] Santhi Chinthala, Ramesh Mande, Suneetha Manne and Sindhura Vemuri,” Sentiment Analysis on Twitter Streaming Data”, Springer International Publishing Switzerland, pp. 161-168, 2015.
[16] Pablo Gamallo, Marcos Garcia, “Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets” Proceedings of the 8th International Workshop on Semantic Evaluation, pp: 171–175, Dublin, Ireland, 2014.
[17] Dhanashri Chafale , Amit Pimpalkar, “Review on Developing Corpora for Sentiment Analysis Using Plutchik’s Wheel of Emotions with Fuzzy Logic”, International Journal of Computer Sciences and Engineering”, pp. 14-18, 2014.