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2016 International Conference on Big Data and Smart Computing (BigComp) (2016)
Hong Kong, China
Jan. 18, 2016 to Jan. 20, 2016
ISSN: 2375-9356
ISBN: 978-1-4673-8795-8
pp: 415-418
Hyo Jin Do , School of Computing, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
Chae-Gyun Lim , School of Computing, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
You Jin Kim , School of Computing, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
Ho-Jin Choi , School of Computing, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
ABSTRACT
Social media has emerged as an effective source to investigate people's opinions in the context of a variety of topics and situations. In particular, many recent studies try to investigate social media during the crisis situations that range from natural disasters to man-made conflicts. In this paper, we investigate people's emotional responses expressed on Twitter during the 2015 Middle East Respiratory Syndrome (MERS) outbreak in South Korea. Specifically, we first present an emotion analysis method to classify fine-grained emotions in Korean Twitter posts. Then, we conduct a case study of how Korean Twitter users responded to MERS outbreak using our emotion analysis method. Experimental results on Korean benchmark dataset demonstrate the superior performance of the proposed emotion analysis approach on real-world dataset. Moreover, our analysis results on tweets related to MERS outbreak help to understand the behaviors of humans and the characteristics of sociocultural system. Further, our method can be harnessed by the media to automatically investigate public opinions as well as the authorities to gain insights for quickly deciding the assistance policies.
INDEX TERMS
Twitter, Media, Support vector machines, Government, Earthquakes, Market research, Hospitals
CITATION

Hyo Jin Do, Chae-Gyun Lim, You Jin Kim and Ho-Jin Choi, "Analyzing emotions in twitter during a crisis: A case study of the 2015 Middle East Respiratory Syndrome outbreak in Korea," 2016 International Conference on Big Data and Smart Computing (BigComp)(BIGCOMP), Hong Kong, China, 2016, pp. 415-418.
doi:10.1109/BIGCOMP.2016.7425960
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