SURVEY ON SENTIMENT ANALYSIS OF STOCK MARKET
DOI:
https://doi.org/10.29121/granthaalayah.v5.i4RACSIT.2017.3354Keywords:
Support Vector Machine, NaiveBayes, K-Nearest NeighbourAbstract [English]
Sentiment analysis has seen a tremendous growth in the past few years. Sentiment analysis or opinion mining is a process of collecting users’ opinion from user generated content. It has various applications, such as stock market prediction, products’ review collection, etc. a large amount of work has been done in this field by applying sentiment analysis to various applications. The main goal of this paper is to study the various methods used for sentiment analysis. Further we explain the overview of various related papers and their performances.
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References
Manisha Shinde-Pawar,”Formation of Smart Sentiment Analysis Technique for Big Data”,International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 2, Issue 12, December 2014
Kim Schouten and Flavius Frasincar, “Survey on aspect-level sentiment analysis”, IEEE Transactions on Knowledge and Data Engineering, Volume: 28, Issue: 3, March 1 2016 DOI: https://doi.org/10.1109/TKDE.2015.2485209
E.VanKleef, H. C. M. Van Trijp, and P. Luning, “Consumer research in the early stages of new product development: a critical review of methods and techniques,” food quality preference, Vol. 16, no. 3, pp. 181–201, 2005. DOI: https://doi.org/10.1016/j.foodqual.2004.05.012
Y. Chen and J. Xie, “Online Consumer review: word-of-mouth as a new element of Marketing Communication mix,” manage. sci., Vol. 54, no. 3, pp. 477–491, 2008. DOI: https://doi.org/10.1287/mnsc.1070.0810
MichałSkuza, Andrzej Romanowski, “Sentiment Analysis of Twitter Data within Big Data Distributed Environment for Stock Prediction”, Proceedings of the Federated Conference on Computer Science and Information Systems pp. 1349–1354 ACSIS, Vol. 5.
AddlightMukwazvure, K.P, Supreethi, AddlightMukwazvure, K.P Supreethi,” A Hybrid Approach to Sentiment Analysis of News Comments”.
B. Pang and L. Lee, “Opinion mining and sentiment analysis,” found. trends inf. retrieval, vol. 2, no. 1-2, pp. 1–135, 2008. DOI: https://doi.org/10.1561/1500000011
AsmitaDhokrat, Sunil Khillare, C. NamrataMahender, “Review on techniques and tools used for opinion mining”, international journal of computer applications technology and research volume 4– issue 6, 419 - 424, 2015 DOI: https://doi.org/10.7753/IJCATR0406.1001
Laura Cruz, Jose Ochoa, Mathieu Roche, Pascal Poncelet, “Dictionary-based Sentiment Analysis applied to specific domain using a Web Mining Approach”
Indurkhya, N. &Damerau, F.J. [eds.] Liu, B., 2010 “Sentiment Analysis and subjectivity,” appeared in handbook of natural language processing. DOI: https://doi.org/10.1201/9781420085938
Bing l., 2012 “Sentiment analysis and opinion mining,” Morgan & Claypool publishers.
M. Tsytsarau and T. Palpanas, “Survey on mining subjective data on the web,” data mining know. discovery, vol. 24, no. 3, pp. 478–514, 2012. DOI: https://doi.org/10.1007/s10618-011-0238-6
Douglas R, Rice Christopher, “Corpus-based dictionaries for Sentiment Analysis of specialized Vocabularies”version 0.1 September 19, 2013
ReshmaBhonde, Binita Bhagwat , SayaliIngulkar, ApekshaPande, “Sentiment Analysis based on dictionary approach”, International Journal of Emerging Engineering Research and Technology Volume 3, issue 1, January 2015
Pravesh Kumar Singh, MohdShahid Husain,” Methodological Study of Opinion Mining and Sentiment Analysis Techniques”, International Journal on Soft Computing (ijsc) vol. 5, no. 1, February 2014 DOI: https://doi.org/10.5121/ijsc.2014.5102
PhayungMeesad and Jiajia Li, King Mongkut's, “Stock Trend Prediction Relying on Text Mining and Sentiment Analysis with Tweets”
VaanchithaKalyanaraman, Sarah Kazi, Rohan Tondulkar,”Sentiment Analysis on News Articles for Stocks”.
PhayungMeesad and Jiajia Li,” Stock Trend Prediction Relying on Text Mining and Sentiment Analysis withTweets”
Johan Bollen,HuinaMao,Xiao-Jun Zeng,” Twitter mood predicts the stock market”
Feifei Xu and VladoKeˇselj,”Collective Sentiment Mining of Microblogs in 24-hour Stock Price MovementPrediction”, 2014 IEEE 16th Conference on Business Informatics
YahyaEruCakra,BayuDistiawanTrisedya,” Stock price prediction using linear regression based on sentiment analysis”, Advanced Computer Science and Information Systems (ICACSIS), 2015 International Conference. DOI: https://doi.org/10.1109/ICACSIS.2015.7415179
Alexander Porshnev, Ilya Redkin, Alexey Shevchenko,”Machine learning in prediction of stock market indicators based on historical dataand data from Twitter sentiment analysis”, 2013 IEEE 13th International Conference on Data Mining Workshops DOI: https://doi.org/10.1109/ICDMW.2013.111
AddlightMukwazvure,K.PSupreethi,”A Hybrid Approach to Sentiment Analysis of NewsComments”
PhayungMeesad, Jiajia Li, “Stock trend prediction relying on text mining and sentiment analysis with tweets”,2014 4th World Congress on Information and Communication Technologies (WICT 2014) DOI: https://doi.org/10.1109/WICT.2014.7077275
Kaihui Zhang, Lei Li, Peng Li,”Stock trend forecasting method based on sentiment analysis and system similarity model”,Strategic Technology (IFOST), 2011 6th International Forum. DOI: https://doi.org/10.1109/IFOST.2011.6021163
Rajat Ahuja, HarshilRastogi,ArpitaChoudhuri,” Stock market forecast using sentiment analysis”, Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference
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