Understanding the shifting nature of fake news research: Consumption, dissemination, and detection

消费(社会学) 假新闻 信息传播 计算机科学 数据科学 万维网 社会学 互联网隐私 社会科学
作者
Rona Nisa Sofia Amriza,Tzu‐Chuan Chou,Wiwit Ratnasari
出处
标识
DOI:10.1002/asi.24980
摘要

Abstract Fake news on social media spreads faster and has become a major societal concern, prompting numerous publications and knowledge sharing among researchers. This research aims to understand the shifting nature of fake news by investigating the citation relationships between significant publications using key route main path analysis (MPA). The process involves generating keywords, collecting and selecting relevant data, and conducting MPA on fake news in social media. The study analyzes 4.057 publications from 2010 to 2023, identifying 27 influential works shaping the knowledge diffusion in fake news research. Findings reveal two main phases: understanding fake news consumption patterns and analyzing its dissemination and detection mechanisms. Through multiple‐global MPA, five research trends are identified: health misinformation, fact‐checking, sharing behavior, fake news recognition, and physiological interventions. The study shows a continuous rise in publications and citations, with current trends focusing on health‐related misinformation. This analysis offers insights into the development and diffusion of fake news topics on social media, emphasizing the importance of historical development in guiding future research by uncovering current trends. Highlighting the historical progression of research provides valuable context, enabling a more nuanced understanding of the field.
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