Twitter sentiment analysis offers organizations an ability to monitor public feeling towards the products and events related to them in real time. Public and private opinion about a wide variety of subjects are expressed and spread continually via numerous tweets. It offers organizations a fast and more effective way to analyze customer’s perspectives towards the success in the market place. Sentiment analysis is an approach to be used to computationally measure customer’s perceptions to a vast extent. This is a survey on the design of a sentiment analysis. After extraction of a vast amount of tweets, it classifies perspectives of customers via tweets into positive and negative sentiments. Which is obtained after classifying the data by using classification approaches like for example Bayes Naïve, Linear Regression, etc.

Twitter, sentiment analysis, datasets, pre-processing, feature extraction, classification

[1] A. K. Jose, N. Bhatia, and S. Krishna, “TwitterSentimentAnalysis”. NationalInstituteof TechnologyCalicut, 2010.
[2] M. Comesaña, A. P.Soares, M.Perea, A.P. Piñeiro, I. Fraga, and A. Pinheiro, “ Author ’ s personal copy Computers in Human Behavior ERP correlates of masked affective priming with emoticons,” Computers in Human Behavior, 29, 588–595, 2013
[3] S.Lohmann, M. Burch, H. Schmauder and D. Weiskopf, “Visual Analysis of Microblog Content Using Time-Varying Co-occurrence Highlighting in Tag Clouds,” Annual conference of VISVISUS. Germany: University of Stuttgart, 2012.
[4] D. Osimo, and F. Mureddu, “Research Challenge on Opinion Mining and Sentiment Analysis,” Proceeding of the 12th conference of Fruct association, 2010, United Kingdom.
[5] A. Pak, and P. Paroubek, “Twitter as a Corpus for Sentiment Analysis and Opinion Mining,” Special Issue of International Journal of Computer Application, France: Universitede Paris-Sud, 2010.
[6] M.Rambocas, and J. Gama, “Marketing Research: The Role of Sentiment Analysis”. The 5th SNA-KDD Workshop’11. Universityof Porto, 2013.
[7] H. Saif, Y.He, and H. Alani, “SemanticSentimentAnalysisof Twitter,” Proceeding of the Workshop on Information Extraction and Entity Analytics on Social Media Data. United Kingdom: Knowledge Media Institute, 2011.
[8]P.Lai,“ExtractingStrongSentimentTrendfromTwitter”. Stanford University, 2012.
[9] Y. Zhou, and Y. Fan, “A Sociolinguistic Study of American Slang,” Theory and Practice in Language Studies, 3(12), 2209–2213, 2013. doi:10.4304/tpls.3.12.2209-2213
[10] A.H.Huang, D.C. Yen, & X. Zhang, “Exploring the effects of emoticons,” Information & Management, 45(7), 466–473, 2008.
[11] D. Boyd, S. Golder & G. Lotan, “Tweet, tweet, retweet: Conversational aspects of retweeting on twitter,” System Sciences (HICSS),2010.
[12] Fox C. (1992). "Information retrieval data structures and algorithms". Lexical Analysis and Stoplists, pp.102–130, 1992.
[13] Go A, Bhayani R, & Huang L. "Twitter sentiment classification using distant supervision". CS224N Project Report, Stanford, 2009
[14] Saif H, He Y, & Alani H. "Alleviating Data Sparsity for Twitter Sentiment Analysis". In Proc. CEUR Workshop Proceedings, 2012.
[15] A. Bakliwal, P. Arora, S. Madhappan, N. Kapre, M. Singh, & V. Varma. "Mining sentiments from tweets". In Proc. the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis, Association for Computational Linguistics, Jeju, Korea, pp.11–18, 2012.
[16] Saif H, Fern M, & He Y. "Evaluation Datasets for Twitter Sentiment Analysis A survey and a new dataset the STS-Gold". Proc. 1st ESSEM Workshop. Turin, Italy, 2013.
[17] Sascha Narr, Michael Hulfenhaus & Sahin Albayrak. "Language-Independent Twitter Sentiment Analysis." 2014.
[18] V. Nareyko, “Why python is perfect for startups,”
[19] H.M.Wallach,“Topic modeling: beyond bag-of-words,” in Proceedings of the 23rd International Conference on Machine Learning (ICML `06), pp. 977–984, Pittsburgh, Pa, USA, June 06.
[20] A. Sweigart, “Invent your own computer games with Python. 2nd edition, 2012.
[21] C. Seberino, “Python. Faster and easier software development,” Annual Conference. California: San Diego, 2012.
[22] A.Lukaszewski, “MySQL for Python. Integrate the flexibility of Python and the power of MySQL to boost the productivity of your applications,” UK: Birningham. Packt Publishing Ltd, 2010.
[23] Gimpel, K., Schneider, N., O‘Connor, B., Das, D., Mills, D., Eisenstein, J., etal. ―Part-of-speech tagging for twitter: Annotation, features, and experiments‖. In Proceedings of the 49th annual meeting of the association for computational linguistics: Human language technologies: Short papers - volume 2 HLT ‘11,pp. 42–47,2011.
[24] P. Bhoir, S. Kolte, “Sentiment Analysis of Movie Reviews using Lexicon approach”, IEEE International Conference on Computational Intelligence and Computing Research, Madurai pp.1-6, 2015.