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http://dx.doi.org/10.22156/CS4SMB.2019.9.11.081

Social Issue Analysis Based on Sentiment of Twitter Users  

Kim, Hannah (Department of Future Convergence Technology, Soonchunhyang University)
Jeong, Young-Seob (Department of Bigdata Engineering, Soonchunhyang University)
Publication Information
Journal of Convergence for Information Technology / v.9, no.11, 2019 , pp. 81-91 More about this Journal
Abstract
Recently, social network service (SNS) is actively used by public. Among them, Twitter has a lot of tweets including sentiment and it is convenient to collect data through open Aplication Programming Interface (API). In this paper, we analyze social issues and suggest the possibility of using them in marketing through sentimental information of users. In this paper, we collect twitter text about social issues and classify as positive or negative by sentiment classifier to provide qualitative analysis. We provide a quantitative analysis by analyzing the correlation between the number of like and retweet of each tweet. As a result of the qualitative analysis, we suggest solutions to attract the interest of the public or consumers. As a result of the quantitative analysis, we conclude that the positive tweet should be brief to attract the users' attention on the Twitter. As future work, we will continue to analyze various social issues.
Keywords
Social network service; Twitter; Sentiment classification; Social issues analysis; Convolutional neural networks;
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Times Cited By KSCI : 9  (Citation Analysis)
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