The Journal of Information Systems (한국정보시스템학회지:정보시스템연구)

Korea Association of Information Systems (한국정보시스템학회)
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Fake News Detection on Social Media using Video Information: Focused on YouTube

영상정보를 활용한 소셜 미디어상에서의 가짜 뉴스 탐지: 유튜브를 중심으로

  • 장윤호 (바이브컴퍼니 S.C.I연구소) ;
  • 최병구 (국민대학교 AI빅데이터융합경영학과)
  • Received : 2023.05.12
  • Accepted : 2023.06.12
  • Published : 2023.06.30
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Abstract

Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

Keywords

Acknowledgement

심사과정에서 두 분의 심사위원과 편집위원장이 제시한 많은 유용한 의견과 제안은 본 연구의 향상에 기여하였음. 본 연구는 2020년 추계 경영정보학회 학술대회 논문을 수정 및 보완하여 확장된 연구임.

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