Deciphering Public Opinion of Nuclear Energy on Twitter

被引:10
|
作者
Khatua, Aparup [1 ]
Cambria, Erik [1 ]
Ho, Shirley S. [1 ]
Na, Jin Cheon [1 ]
机构
[1] Nanyang Technol Univ, Singapore, Singapore
关键词
nuclear energy; public opinion mining; artificial intelligence; SENTIMENT ANALYSIS; SOCIAL MEDIA;
D O I
10.1109/ijcnn48605.2020.9206903
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper explores nuclear energy-related Twitter discussions as a response to the 2011 Fukushima Nuclear Disaster and the 2017 Nobel Peace Prize won by the International Campaign to Abolish Nuclear Weapons. We have considered a total of 2 million tweets for these two events. In particular, we employed CNN, LSTM, and Bi-LSTM to investigate whether social media users are supportive or cynical about nuclear energy. Our AI algorithms have performed better for polarity detection (accuracy in the range of 90%) with respect to subjectivity detection (accuracy in the range of 75%). We also note that dominant aspects of supporting tweets revolve around concepts like clean energy, lower CO2 emission, and sustainable future. On the contrary, cynical users see nuclear energy as a threat to the environment, human life, and safety.
引用
收藏
页数:8
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