How does the development of COVID-19 affect the public's engagement to fake news rebuttal microblogs?

IF 7.6 2区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Telematics and Informatics Pub Date : 2023-10-01 DOI:10.1016/j.tele.2023.102029

Zongmin Li , Ye Zhao , Xinyu Du , Shihang Wang , Yanfang Ma , Yi Zhang

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引用次数: 0

Abstract

COVID-19 infodemics are intertwined with the dynamic development of the pandemic. During infodemics, the challenges and difficulties are to reveal the dynamic evolution of public’s engagement to fake news rebuttals information and break through the bottleneck of previous static research. Motivated by this, fake news rebuttals engagement index (FNREI) is proposed to state the public engagement towards COVID-19 related fake news rebuttals. A total of 19,603 fake news rebuttals microblogs from Weibo are divided into four categories by latent dirichlet allocation (LDA): “status and confirmed cases of COVID-19″, ”transmission mode and living conditions of coronavirus“, ”prevention and detection of COVID-19″ and “overseas fake news and derivative events”. Time-varying parameter vector auto-regressive model (TVP-VAR) is used to explore the time-varying impact of the COVID-19 life cycle and the appearance of virus mutation (Delta, Omicron) on four categories of FNREI time series. The research results suggest that under the impact of different major events during the COVID-19 life cycle, the public's engagement to different categories of COVID-19 related fake news has different priorities, its duration and intensity is dynamically changing. This study explores the evolution of individuals’ engagement to fake news rebuttals information during the COVID-19 and provides a basis for improving fake news governance effectiveness.

查看原文本刊更多论文

COVID-19的发展如何影响公众对假新闻的微博参与?

COVID-19疫情与大流行的动态发展交织在一起。在信息传播过程中，如何揭示公众对假新闻参与的动态演变，突破以往静态研究的瓶颈是挑战和难点。基于此，我们提出假新闻反驳参与指数(FNREI)来描述公众对新冠肺炎相关假新闻反驳的参与程度。通过潜狄利克雷分配(latent dirichlet allocation, LDA)将微博上的19603条假新闻反驳微博分为“新冠病毒现状及确诊病例″”、“新冠病毒传播模式及生存条件”、“新冠病毒的预防与检测″”和“海外假新闻及衍生事件”四类。采用时变参数向量自回归模型(TVP-VAR)探讨新冠肺炎生命周期和病毒突变(Delta、Omicron)的出现对四类FNREI时间序列的时变影响。研究结果表明，在新冠肺炎生命周期不同重大事件的影响下，公众对不同类别新冠肺炎相关假新闻的参与具有不同的优先级，其持续时间和强度是动态变化的。本研究探讨新冠肺炎疫情期间个人对假新闻反驳信息参与的演变，为提高假新闻治理有效性提供依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Telematics and Informatics INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

17.00

自引率

4.70%

发文量

104

审稿时长

24 days

期刊介绍： Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.