Abstract
Social media locales (akin Twitter, Facebook, microblogs etc.) are a global platform to share interesting ideas or news, comments, and reviews. However, feedbacks via sharing of thoughts, feelings, and comments about various products and services become key characteristics on which business in the contemporary world rely on. These are called as sentiments on social media. An attitude, believe, or acumen driven by feeling collectively called sentiment. Sentiment analysis otherwise called as opinion mining studies individuals’ sentiments pointing certain elements. Web is a resourceful place for sentiment information. Difficulty arises when the phrases containing homographs are encountered. In this paper, a brief review of work done on sentiment analysis on social media applications along with various phases and levels of sentiment analysis has been discussed.
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References
Jin Z, Yang Y, Bao X, Huang B (2016) Combining user-based and global lexicon features for sentiment analysis in Twitter. IEEE. 978-1-5090-0620-5
Trupthi M, Pabboju S (2017) Sentiment analysis on Twitter using streaming API. IEEE. 978-1-5090-1560-3
Jose R, Chooralil VS (2015) Prediction of election result by enhanced sentiment analysis on Twitter data using word sense disambiguation. IEEE. 978-1-4673-7349-4
Zamani NAM, Abidin SZZ, Omar N, Abiden MZZ (2013) Sentiment analysis: determining people’s emotions in Facebook. ISBN 978-960-474-368-1
Chang S (2016) Instagram post data analysis. arXiv:1610.02445v1
Kharde VA, Sonawane SS (2016) Sentiment analysis of Twitter data: a survey of techniques. Int J Comput Appl 139(11)
Arora D, Li KF, Neville SW (2015) Consumers’ sentiment analysis of popular phone brands and operating system preference using Twitter data: a feasibility study. IEEE. 1550-445X
Godsay M (2015) The process of sentiment analysis: a study. Int J Comput Appl 126(7)
Medhat W, Hassan A, Korashy H (2014) Sentiment analysis algorithm and applications: a Survey. Ain Shams Eng J 5
Eshleman RM, Yang H (2014) A spatio-temporal sentiment analysis of Twitter data and 311 civil complaints. IEEE, 978-1-4799-6719-3
Gokulakrishnan B, Priyanthan P, Ragavan T, Prasath N, Perera A (2012) Opinion mining and sentiment analysis on a Twitter data stream. IEEE, ICTer, pp 182–188
Grandin P, Adán JM (2016) Piegas: a system for sentiment analysis of tweets in Portuguese. IEEE Lat Am Trans 14(7)
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Akankasha, Arora, B. (2019). A Review of Sentimental Analysis on Social Media Application. In: Rathore, V., Worring, M., Mishra, D., Joshi, A., Maheshwari, S. (eds) Emerging Trends in Expert Applications and Security. Advances in Intelligent Systems and Computing, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-2285-3_56
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DOI: https://doi.org/10.1007/978-981-13-2285-3_56
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