Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Quantifying and Analyzing Vocal Emotion of COVID-19 News Speech Across Broadcasters in South Korea and the United States Based on CNN

한국과 미국 방송사의 코로나19 뉴스에 대해 CNN 기반 정량적 음성 감정 양상 비교 분석

  • Nam, Youngja (Humanities Research Institute, Chung-Ang University) ;
  • Chae, SunGeu (Department of Industrial Engineering, Hyanyang University)
  • Received : 2022.01.04
  • Accepted : 2022.01.24
  • Published : 2022.02.28
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Abstract

During the unprecedented COVID-19 outbreak, the public's information needs created an environment where they overwhelmingly consume information on the chronic disease. Given that news media affect the public's emotional well-being, the pandemic situation highlights the importance of paying particular attention to how news stories frame their coverage. In this study, COVID-19 news speech emotion from mainstream broadcasters in South Korea and the United States (US) were analyzed using convolutional neural networks. Results showed that neutrality was detected across broadcasters. However, emotions such as sadness and anger were also detected. This was evident in Korean broadcasters, whereas those emotions were not detected in the US broadcasters. This is the first quantitative vocal emotion analysis of COVID-19 news speech. Overall, our findings provide new insight into news emotion analysis and have broad implications for better understanding of the COVID-19 pandemic.

전례 없는 코로나19 팬데믹 상황에서 대중의 정보에의 요구는 과도한 코로나19 뉴스 소비를 조장하였다. 뉴스는 대중의 심리적 안녕에도 영향을 미치기에 뉴스 보도 양태에 대한 각별한 주의가 요구된다. 이에 본 연구는 한국과 미국의 주요 뉴스 미디어의 코로나19 관련 뉴스의 음성 감정 양상을 합성곱 신경망에 기반하여 분석하였다. 분석 결과, 대부분의 뉴스 미디어에서 중립이 탐지되었으나 슬픔과 분노도 탐지되었다. 이러한 양상은한국의 뉴스 미디어에서 두드러진 반면 미국 뉴스 미디어에서는 나타나지 않았다. 본 연구는 코로나19 뉴스의 첫 음성 감정 분석 연구로, 뉴스의 감정 분석에 있어 새로운 방향을 제시할 뿐 아니라 팬데믹에 대한 이해 증진에 있어 광범위한 함의를 지닌다.

Keywords

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538).

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