A Computational Framework for Understanding Firm Communication During Disasters

Bei Yan; Feng Mai; Chaojiang Wu; Rui Chen; Xiaolin Li

doi:10.1287/isre.2022.0128

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. Large firms are leaders in disaster response and communication. We study how firms communicate on social media during various disasters and the relationship between their communication and public engagement using a computationally intensive theory construction framework. The framework incorporates a novel natural language processing (NLP) approach, Semantic Projection with Active Retrieval (SPAR), as a key component of the method lexicon. Drawing on the two dimensions (internal versus external and stable versus flexible) of the Competing Values Framework (CVF) as our theoretical lexicon, we examine Facebook posts of Russell 3000 firms on multiple disasters between 2009 and 2022. We find that social media messages that are internal- and stable-oriented, or emphasize operational continuity, are more likely to elicit engagement from the public during biological disasters. By contrast, messages that are external- and flexible-oriented, or stress the innovations to adapt to the disaster, induce more engagement in weather-related disasters. The study offers theoretical implications and methodological support for the research and design of social media messages in disasters and other contexts. History: This paper has been accepted for the Information Systems Research Special Section on Unleashing the Power of Information Technology for Strategic Management of Disasters. Ahmed Abbasi, Robin Dillon-Merrill, H. Raghav Rao, Olivia Sheng, Senior Editors; Han-fen Hu, Associate Editor. Funding: This work was supported by the National Science Foundation (Grant 2020203). Supplemental Material: The e-companion is available at https://doi.org/10.1287/isre.2022.0128 .

A Computational Framework for Understanding Firm Communication During Disasters

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