Long-Term Trends in Public Sentiment in Indian Demonetisation Policy

被引:1
|
作者
Darliansyah, Adi [1 ]
Wandabwa, Herman Masindano [1 ]
Naeem, M. Asif [1 ]
Mirza, Farhaan [1 ]
Pears, Russel [1 ]
机构
[1] Auckland Univ Technol, Auckland, New Zealand
关键词
Government policy; Sentiment analysis; Twitter mining; Rapid Miner;
D O I
10.1007/978-981-13-6052-7_6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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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页码:65 / 75
页数:11
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