Signals of Transition in Support Systems: A Study of the use of Social Media Analytics in Crisis Management

In crisis informatics, little attention is placed on how transitions occur between periods of crisis and non-crisis. The analysis of transition behaviors in public organizations could help in understanding the duality between the need for continuity of services provided to the community, and the cyclical nature of risk and crisis management. This study uniquely highlights the transitions occurring when organizations need to stop day-to-day activities to focus on responding to a crisis while continuing to provide services to their communities. We focus on the use of social media analytics as a support system to study transitions and, with the objective to gain an insight into how sociotechnical systems navigate through periods of crisis and non-crisis, we leverage individual experiences of use of social media as a source of information in public service organizations and developers of social media analytics support tools. In doing so, we employed a process study approach, conducted semi-structured interviews, and used thematic analysis to trace patterns of transitions between crisis and non-crisis states. Furthermore, we formulate five signals that public organizations exhibit to illustrate and guide organizational transition behaviors. The main contribution of this study is the explanation and conceptualization of how transitions happen by framing social media as a support information system. In addition, we highlight the return to a new steady state, an overlooked area of organizational transitions and continuity. Our study will help streamline processes of continuity in organizations and inspires the design and improvement of current and future support systems. Future research could apply and extend our propositions to other support systems such as geospatial technologies, robots, and even artificial intelligence.

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Publication Details

Journal
ACM Transactions on Social Computing
Published
2024-08-21
DOI
https://doi.org/10.1145/3649474
Citations
3
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
3.40
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article

Signals of Transition in Support Systems: A Study of the use of Social Media Analytics in Crisis Management

Tim A. Majchrzak, Devinder Thapa, Lucia Castro Herrera, Terje Gjøsæter
3 citations
ACM Transactions on Social Computing
Disaster Management and Resilience
3.40
article

Signals of Transition in Support Systems: A Study of the use of Social Media Analytics in Crisis Management

Tim A. Majchrzak, Devinder Thapa, Lucia Castro Herrera, Terje Gjøsæter
article en
3 citations

Abstract

In crisis informatics, little attention is placed on how transitions occur between periods of crisis and non-crisis. The analysis of transition behaviors in public organizations could help in understanding the duality between the need for continuity of services provided to the community, and the cyclical nature of risk and crisis management. This study uniquely highlights the transitions occurring when organizations need to stop day-to-day activities to focus on responding to a crisis while continuing to provide services to their communities. We focus on the use of social media analytics as a support system to study transitions and, with the objective to gain an insight into how sociotechnical systems navigate through periods of crisis and non-crisis, we leverage individual experiences of use of social media as a source of information in public service organizations and developers of social media analytics support tools. In doing so, we employed a process study approach, conducted semi-structured interviews, and used thematic analysis to trace patterns of transitions between crisis and non-crisis states. Furthermore, we formulate five signals that public organizations exhibit to illustrate and guide organizational transition behaviors. The main contribution of this study is the explanation and conceptualization of how transitions happen by framing social media as a support information system. In addition, we highlight the return to a new steady state, an overlooked area of organizational transitions and continuity. Our study will help streamline processes of continuity in organizations and inspires the design and improvement of current and future support systems. Future research could apply and extend our propositions to other support systems such as geospatial technologies, robots, and even artificial intelligence.

ACM Transactions on Social ComputingVol. 8(1-2)
University of Agder (NO)
Openalex Percentile: Top 7%
Disaster Management and Resilience
3.40
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