Varieties of corona news: a cross-national study on the foundations of online misinformation production during the COVID-19 pandemic.

IF 2 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2023-01-01 Epub Date: 2022-12-13 DOI:10.1007/s42001-022-00193-5
Cantay Caliskan, Alaz Kilicaslan
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引用次数: 0

Abstract

Misinformation in the media is produced by hard-to-gauge thought mechanisms employed by individuals or collectivities. In this paper, we shed light on what the country-specific factors of falsehood production in the context of COVID-19 Pandemic might be. Collecting our evidence from the largest misinformation dataset used in the COVID-19 misinformation literature with close to 11,000 pieces of falsehood, we explore patterns of misinformation production by employing a variety of methodological tools including algorithms for text similarity, clustering, network distances, and other statistical tools. Covering news produced in a span of more than 14 months, our paper also differentiates itself by its use of carefully controlled hand-labeling of topics of falsehood. Findings suggest that country-level factors do not provide the strongest support for predicting outcomes of falsehood, except for one phenomenon: in countries with serious press freedom problems and low human development, the mostly unknown authors of misinformation tend to focus on similar content. In addition, the intensity of discussion on animals, predictions and symptoms as part of fake news is the biggest differentiator between nations; whereas news on conspiracies, medical equipment and risk factors offer the least explanation to differentiate. Based on those findings, we discuss some distinct public health and communication strategies to dispel misinformation in countries with particular characteristics. We also emphasize that a global action plan against misinformation is needed given the highly globalized nature of the online media environment.

Supplementary information: The online version contains supplementary material available at 10.1007/s42001-022-00193-5.

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日冕新闻的多样性:关于 COVID-19 大流行期间网络错误信息生产基础的跨国研究。
媒体中的错误信息是由个人或集体采用的难以测量的思维机制产生的。在本文中,我们将揭示 COVID-19 大流行背景下产生虚假信息的特定国家因素。我们从 COVID-19 虚假信息文献中使用的最大的虚假信息数据集(包含近 11,000 条虚假信息)中收集证据,并通过使用文本相似性算法、聚类、网络距离和其他统计工具等多种方法工具来探索虚假信息的生产模式。我们的论文涵盖了 14 个多月内产生的新闻,其与众不同之处还在于,我们对虚假信息的主题进行了精心控制的手工标记。研究结果表明,国家层面的因素并不能为预测虚假信息的结果提供最有力的支持,但有一个现象除外:在新闻自由问题严重、人类发展水平较低的国家,虚假信息的作者大多不为人知,他们往往关注类似的内容。此外,作为虚假新闻的一部分,对动物、预测和症状的讨论强度是国家间最大的区别因素;而对阴谋、医疗设备和风险因素的新闻提供的区别解释最少。基于这些发现,我们讨论了一些独特的公共卫生和传播策略,以消除具有特殊性的国家的错误信息。我们还强调,鉴于网络媒体环境的高度全球化性质,需要制定一项打击误导的全球行动计划:在线版本包含补充材料,可在 10.1007/s42001-022-00193-5 上查阅。
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
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
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