A Computational Framework for Understanding Firm Communication During Disasters

IF 5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Information Systems Research Pub Date : 2023-11-07 DOI:10.1287/isre.2022.0128
Bei Yan, Feng Mai, Chaojiang Wu, Rui Chen, Xiaolin Li
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引用次数: 1

Abstract

Firms’ public communication on social media during disasters can benefit both disaster response efficiency and the perception of the corporate image. Despite its importance, limited guidelines are available to inform firms’ disaster communication strategies. The current study examines firms’ communication on social media in various disasters and how it impacts public engagement. We employ a novel natural language processing (NLP) approach, Semantic Projection with Active Retrieval (SPAR), to analyze Facebook posts made by Russell 3000 firms between 2009 and 2022 concerning various disasters. We show that firm communication can be measured based on two dimensions derived from the Competing Values Framework (CVF): internal versus external and stable versus flexible. We find that social media messages that emphasize operational continuity (internal/stable-oriented) are more popular during biological disasters. By contrast, messages that stress innovations and adaptations to disasters (external/flexible-oriented) elicit more engagement in weather-related disasters. The study offers a framework to characterize and guide firms’ design of disaster communication on social media in different disaster contexts. Our SPAR method is also available to firms to analyze their social media data and uncover the underlying patterns in communication across different contexts.
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理解灾难期间企业沟通的计算框架
企业在灾害中通过社交媒体进行公众沟通,既有利于提高灾害响应效率,也有利于提升企业形象。尽管它很重要,但有限的指导方针可以为公司的灾难沟通策略提供信息。目前的研究调查了企业在各种灾难中在社交媒体上的沟通,以及它如何影响公众参与。我们采用了一种新颖的自然语言处理(NLP)方法,语义投影与主动检索(SPAR),来分析罗素3000公司在2009年至2022年间发布的关于各种灾难的Facebook帖子。我们表明,企业沟通可以基于竞争价值框架(CVF)衍生的两个维度来衡量:内部与外部、稳定与灵活。我们发现,强调运营连续性(内部/稳定导向)的社交媒体信息在生物灾害期间更受欢迎。相比之下,强调创新和适应灾害(外部/灵活导向)的信息会促使人们更多地参与与天气有关的灾害。该研究提供了一个框架来描述和指导企业在不同灾害背景下的社交媒体灾难传播设计。我们的SPAR方法也可用于企业分析其社交媒体数据,并揭示不同背景下沟通的潜在模式。
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来源期刊
CiteScore
9.10
自引率
8.20%
发文量
120
期刊介绍: ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.
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