Research on Public Environmental Perception of Emotion, Taking Haze as an Example

Qiang Bao, Xujuan Zhang, Xijuan Wu, Qiang Zhang and Jinshou Chen
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Qiang Bao: College of Computing, Illinois Institute of Technology, Chicago, IL 60616, USA
Xujuan Zhang: College of Computer Science & Artificial Intelligence, Lanzhou Institute of Technology, Lanzhou 730050, China
Xijuan Wu: Department of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China
Qiang Zhang: Department of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China
Jinshou Chen: Department of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China

IJERPH, 2021, vol. 18, issue 22, 1-16

Abstract: Ecological and environmental problems have become increasingly prominent in recent years. Environmental problems represented by haze have become a topic that affects the harmonious ecology of human beings. The trend of this topic is on the rise. People’s perception of the environment after the impact of haze has also changed. A real-time grasp of the dynamic public environment perception of emotions is often an important basis for environmental management departments to effectively solve environmental problems through public opinion. This article focuses on the problem of the public perception of emotional changes, which is caused by fog and hazy weather, proposes an environmental emotion perception model, using Weibo comment data about fog and haze as environmental perception data, and analyzes the impact of fog and haze on the public in four seasonal time dimensions. The post-environment perception of emotion changes: the results show that in spring, the public’s environmental perception of emotions is mainly negative emotions at the beginning of the season; in summer, positive emotions become dominant emotions; in autumn, the public’s environmental perception of emotions is dominated by negative emotions that increase substantially; and in winter, the dominant environmental perception of emotions of the public is still negative. This theory provides support for research on social emotions and public opinion behavior.

Keywords: convolutional neural network; environmental perception of emotion; weighted networks; deep learning (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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