Abstract
Twitter, being one of the popular social media site, is a viable source of data for extracting and analyzing the sentiment of the users. User sentiment varies with their demographic attributes and social background; which results in different sentiment among users for the same event or topic. In this paper an emotion/polarity detection method is proposed, to detect sentiment state of the twitter users. The proposed method is implemented as a web application called “TweeSent”. TweeSent classifies the tweets in terms of emotions and polarity across demographic attributes of the users such as location, age, gender, and occupation class. The demographic attributes of the tweets are estimated by using domain depend dictionaries. In order to evaluate the performance of our system, the tweets on demonetization in India is extracted, analyzed and compared with the government survey reports.
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Swain, S., Seeja, K.R. (2019). TWEESENT: A Web Application on Sentiment Analysis. In: Tiwari, S., Trivedi, M., Mishra, K., Misra, A., Kumar, K. (eds) Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 851. Springer, Singapore. https://doi.org/10.1007/978-981-13-2414-7_36
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DOI: https://doi.org/10.1007/978-981-13-2414-7_36
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