Impact of Artificial Intelligence News Source Credibility Identification System on Effectiveness of Media Literacy Education

Hsu-Cheng Tosti Chiang*, Chih Shan Liao, Wei Ching Wang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

摘要

During presidential elections and showbusiness or social news events, society has begun to address the risk of fake news. The Sustainable Development Goals 4 for Global Education Agenda aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” by 2030. As a result, various nations have deemed media literacy education a required competence in order for audiences to maintain a discerning attitude and to verify messages rather than automatically believing them. This study developed a highly efficient message discrimination method using new technology using artificial intelligence and big data information processing containing general news and content farm message data on approximately 938,000 articles. Deep neural network technology was used to create a news source credibility identification system. Media literacy was the core of the experimental course design. Two groups of participants used different methods to perform message discrimination. The results revealed that the system significantly expanded the participants’ knowledge of media literacy. The system positively affected the participants’ attitude, confidence, and motivation towards media literacy learning. This research provides a method of identifying fake news in order to ensure that audiences are not affected by fake messages, thereby helping to maintain a democratic society.

原文英語
文章編號4830
期刊Sustainability (Switzerland)
14
發行號8
DOIs
出版狀態已發佈 - 2022 4月 1

ASJC Scopus subject areas

  • 地理、規劃與發展
  • 可再生能源、永續發展與環境
  • 環境科學(雜項)
  • 能源工程與電力技術
  • 管理、監督、政策法律

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