Asian Journal of Computer Science and Technology (AJCST)
Classification Techniques on Twitter Data: A ReviewAuthor : S. Shafina Banu, K. Syed Kousar Niasi and E. Kannan
Volume 8 No.2 Special Issue:March 2019 pp 66-69
Data mining is the practice of examining unknown patterns of data according to diverse viewpoints for classification into valuable information, which is composed and gathered in collective areas, such as data warehouses.For effective analysis, data mining algorithms enabling business decision making and other information necessities to eventually cut costs and raise revenue. Sentiment analysis is the method of defining the emotional tone behind a sequence of words, used to gain an accepting of the attitudes, opinions and emotions conveyed within an online mention. Sentiment analysis is tremendously useful in social media observing as it allows us to gain a synopsis of the broader public opinion behind definite topics. The applications of sentiment analysis are extensive and influential. The ability to abstract insights from social data is a practice that is being broadly adopted by organizations across the world. In this paper, we focused on sentiment analysis on the twitter data.
Data Mining, Sentiment Analysis, Social Media, Twitter, Emotions
 Efthymios Kouloumpis, Therasa Wilson and Johanna Moore, “Twitter Sentiment Analysis: The Good the Bad and the OMG!”, Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media., 2011.
 SaraRosenthal, Preslav Nacov, Svetlana kiritchenko, Saif M Mohammad, Alan Ritter, and Veselin Stoyanov,“SemEval-2015Task10: Sentiment Analysis in Twitter”, Proceedings of the 9th International Workshop on Semantic Evaluation., Jun. 2015.
 Sara Rosenthal, Noura Farra, and Preslav Nakov, “SemEval-2017Task4: Sentiment Analysis in Twitter”, Proceedings of the 11th International Workshop on Semantic Evaluations,Aug. 2017.
 Eugenie Martinez Camara, M. Teresa Martin Valdivia, L. Alfonso Urena Lopez, and Arturo Montejo Raez, “Sentiment analysis in Twitter”, Oct. 2012.
 L. Barbosa, and J.Feng, “Robust sentiment detection on twitter from biased and noisy data”, Proceedings of COLING., pp. 36-44, 2010.
 A. Agarwal, B. Xie, I. Vovsha, O. Rambow, and R. Passonneau, “Sentiment analysis of twitter data”,Proc. ACL 2011 Workshop on Languages in Social Media., pp. 30–38, 2011.
 A. Moschitti, “Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees”,M. (eds.) ECML 2006. LNCS (LNAI), Vol. 4212, pp. 318–329,2006.
 M. Speriosu, N. Sudan, S. Upadhyay, and J. Baldridge, “Twitter polarity classification with label propagation over lexical links and the follower graph”, Proceedings of the EMNLP First Workshop on Unsupervised Learning in NLP., pp. 53–63, 2011.
 ChanghuaYang, KevinHsin-YihLin and Hsin-His Chen, “Emotion classification using web blog corpora”, Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence., pp. 275–278, 2007.
 [Online] Available at: https://communications.tufts.edu/marketing-and-branding/social-media-overview/
 GhazalehBeigi, Xia Hu, Ross Maciejewski and Huan Liu, “An Overview of Sentiment Analysis in Social Media and its Applications in Disaster Relief”, Springer, 2016.
 Larry Alton. [Online] Available at: https://www.datasciencecentral.com/profiles/blogs/the-7-most-important-data-mining-techniques, 2017
 Mashael Saeed Alqhtani and M. Rizwan Jameel Qureshi, “Data mining approach for classifying twitter’s users”, International Journal of Computer Engineering & Technology (IJCET), Vol. 8, No.5, Oct. 2017.
 Md. Shoeb and Jawed Ahmed, “Sentiment Analysis and Classification of Tweets Using Data Mining”, International Research Journal of Engineering and Technology (IRJET), Dec. 2017.
 Kirti Huda, Md. Tabrez Nafis and Neshat Karim Shaukat “Classification Technique for Sentiment Analysis of Twitter Data”, International Journal of Advanced Research in Computer Science, Vol. 8, No.5, Jun. 2017.
 Amandeep Kaur, Deepesh Khaneja, Khushboo Vyas, and Ranjit Singh Saini, “Sentiment Analysis on Twitter using Apache Spark”, Advanced Topics in Computer Systems., Oct. 2017.
 Efstratios Kontopoulos, Christos Berberidis, The ologos Dergiades, and Nick Bassiliades, “Ontology-based sentiment analysis on twitter posts”, Expert Systems with Applications,Vol. 40, No.10, pp. 4065-4074, Aug. 2013.