How manipulating information affects information diffusion during disasters: The effects of modifying falsehoods versus corrections

IF 6.8 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Kelvin K. King
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Abstract

Information evolves as it is disseminated on social media. However, studies have largely overlooked a major aspect of the diffusion process: how information is modified, the various dimensions of these modifications, and their roles in the diffusion process. To fill these research gaps, we utilize the Information Manipulation Theory (IMT) as a theoretical lens and a unique panel dataset of 71 falsehoods, propagated during five disasters, to investigate how modifying information affects its diffusion. Our exploratory analysis suggests that at least 65 % of the messages shared are half-truths. Although falsehoods had a higher modification rate for the first 700 h, corrections were modified more aggressively and for 100 h longer after that period, owing to competition. Our empirical analysis suggests that modified information, i.e., information that includes unrelated responses such as deflections, self-referents, additional details, and more information, is generally shared more frequently than unmodified information.
Furthermore, for falsehoods, a one-unit increase in these modifications increases diffusion; however, when manner and quantity modifications increase by one unit for corrections, sharing increases by 115.1 % and 102.2 %, respectively. Although relation modifications from corrections cause an over 149 % increase in sharing at the information diffusion introduction stages, they do not occur in the maturity and decline stages, and are counterproductive in the growth stages. We also find that negatively charged corrections stimulate virality more than positive ones.
These findings have important implications for researchers and decision-makers.
在灾难中操纵信息如何影响信息扩散:修改虚假与更正的效果
信息随着在社交媒体上的传播而演变。然而,研究在很大程度上忽视了传播过程的一个主要方面:信息是如何被修改的,这些修改的各个方面,以及它们在传播过程中的作用。为了填补这些研究空白,我们利用信息操纵理论(IMT)作为理论透镜和在五次灾难中传播的71个虚假信息的独特面板数据集,来研究修改信息如何影响其传播。我们的探索性分析表明,至少65%的分享信息是半真半假的。虽然谎言在前700小时有较高的修改率,但由于竞争,在此之后更正的修改更积极,并且持续时间更长100小时。我们的实证分析表明,修改后的信息,即包含不相关反应的信息,如偏转、自我指涉、附加细节和更多信息,通常比未修改的信息共享得更频繁。此外,对于谎言,这些修改每增加一个单位,就会增加传播;然而,当修正的方式和数量增加一个单位时,共享分别增加115.1%和102.2%。虽然修正带来的关系修正在信息扩散引入阶段会使共享增加149%以上,但在成熟期和衰退期不会发生,在成长阶段会产生反效果。我们还发现,带负电荷的修正比带正电荷的修正更能刺激病毒式传播。这些发现对研究人员和决策者具有重要意义。
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
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
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