Abstract
Social media mining can provide insights into a community’s perceptions which conventional approaches cannot observe. In this paper, we perform a sentiment analysis for measuring long-term trends in public opinion during the 2016 Indian demonetisation policy using Twitter data. We compare our findings to prior research and reports retrieved from media and sources. We utilise Rapid Miner sentiment classifier to a post-event of extending the deadline to deposit the forfeit banknotes. The results indicate an attitude that is predominantly continuing to oppose towards demonetisation policy implementation. We recommend from this study that a multi-lingual sentiment be employed to process non-polarised tweets in local languages in future work.
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Darliansyah, A., Wandabwa, H.M., Naeem, M.A., Mirza, F., Pears, R. (2019). Long-Term Trends in Public Sentiment in Indian Demonetisation Policy. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_6
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DOI: https://doi.org/10.1007/978-981-13-6052-7_6
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