Who do you trust? The digital destruction of shared situational awareness and the COVID-19 infodemic
Open accessAbstract
Developments in centrally managed communications (e.g. Twitter, Facebook) and service (e.g. Uber, airbnb) platforms, search engines and data aggregation (e.g. Google) as well as data analytics and artificial intelligence, have created an era of digital disruption during the last decade. Individual user profiles are produced by platform providers to make money from tracking, predicting, exploiting and influencing their users' decision preferences and behavior, while product and service providers transform their business models by targeting potential customers with more accuracy. There have been many social and economic benefits to this digital disruption, but it has also largely contributed to the digital destruction of mental model alignment and shared situational awareness through the propagation of mis-information i.e. reinforcement of dissonant mental models by recommender algorithms, bots and trusted individual platform users (influencers). To mitigate this process of digital destruction, new methods and approaches to the centralized management of these platforms are needed to build on and encourage trust in the actors that use them (and by association trust in their mental models). The global 'infodemic' resulting from the COVID-19 pandemic of 2020, highlights the current problem confronting the information system discipline and the urgency of finding workable solutions.
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The key to achieving situational awareness is the development and implementation of an accepted approach to complex information governance for response to societal problems and crises.
“The key to achieving this 'situational awareness' is the development and implementation of an accepted approach to complex information governance for response to societal problems and crises (Bunker, 2020;Nüttgens, Gadatsch, Kautz, Schirmer, & Blinn, 2011;Smith & Stirling, 2008).”
From Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action (2022) · cites this paper as Bunker, 2020
In response to any crisis, to develop and deploy resources effectively, an IS must produce an accurate, reliable, and trustworthy assessment of the situation at scale.
“In response to any crisis, however, we know that to develop and deploy resources effectively, an IS must produce an accurate, reliable, and trustworthy assessment of the situation at scale (Bunker, 2020).”
From Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action (2022) · cites this paper as Bunker, 2020
The literature has posited that technology, via extensive use of IS systems and remote sensing devices, provides necessary data to scientists and decision makers at a global level for monitoring and governance of climate change progression.
“The literature has posited the role of technology in the monitoring and governance of climate change progression, via the extensive use of IS systems and remote sensing devices to provide the necessary data to scientists and decision makers at a global level (Bunker, 2020;Nüttgens et al., 2011).”
From Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action (2022) · cites this paper as Bunker, 2020
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Cites
Algorithms of Oppression: How Search Engines Reinforce Racism
Noble, S. U. (2020) · doi:10.2307/j.ctt1pwt9w5 · Cited by 2,709 · see citing works
(2019) · Cited by 2,637 · see citing works
Age of Surveillance Capitalism – The Fight for a Human Future at the New Frontier of Power.
Kendell, D. (2020) · Brock Education Journal · doi:10.26522/brocked.v29i2.849 · Cited by 2,159 · see citing works
Shared Reality: Experiencing Commonality with others' Inner States about the World
Echterhoff, G., Higgins, E. T., & Levine, J. M. (2009) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2009.01161.x · Cited by 676 · see citing works
Algorithms of oppression: how search engines reinforce racism
Sharma, S. (2019) · Ethnic and Racial Studies · doi:10.1080/01419870.2019.1635260 · Cited by 646 · see citing works
Fake news as a two-dimensional phenomenon: a framework and research agenda
Egelhofer, J. L., & Lecheler, S. (2019) · Annals of the International Communication Association · doi:10.1080/23808985.2019.1602782 · Cited by 551 · see citing works
Enke, N., & Borchers, N. S. (2019) · International Journal of Strategic Communication · doi:10.1080/1553118x.2019.1620234 · Cited by 488 · see citing works
Classifying Twitter Topic-Networks Using Social Network Analysis
Himelboim, I., Smith, M. A., Rainie, L., Shneiderman, B., & Espina, C. (2017) · Social Media + Society · doi:10.1177/2056305117691545 · Cited by 338 · see citing works
Sismondo, S. (2017) · Social Studies of Science · doi:10.1177/0306312717692076 · Cited by 312 · see citing works
Tonidandel, S., King, E. B., & Cortina, J. M. (2016) · Organizational Research Methods · doi:10.1177/1094428116677299 · Cited by 201 · see citing works
Lee, A. S., Thomas, M. A., & Baskerville, R. (2014) · Information Systems Journal · doi:10.1111/isj.12054 · Cited by 192 · see citing works
Mirbabaie, M., Bunker, D., Stieglitz, S., Marx, J., & Ehnis, C. (2020) · Journal of Information Technology · doi:10.1177/0268396220929258 · Cited by 192 · see citing works
Self-citationSense‐making in social media during extreme events
Stieglitz, S., Bunker, D., Mirbabaie, M., & Ehnis, C. (2017) · Journal of Contingencies and Crisis Management · doi:10.1111/1468-5973.12193 · Cited by 179 · see citing works
Self-citationLanzing, M. (2018) · Philosophy & Technology · doi:10.1007/s13347-018-0316-4 · Cited by 160 · see citing works
Developing shared situational awareness for emergency management
Seppänen, H., Mäkelä, J., Luokkala, P., & Virrantaus, K. (2013) · Safety Science · doi:10.1016/j.ssci.2012.12.009 · Cited by 107 · see citing works
Elbanna, A. R., Bunker, D., Levine, L., & Sleigh, A. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.01.011 · Cited by 101 · see citing works
Self-citationDefining and Measuring Shared Situational Awareness
Nofi, A. A. (2000) · Defense Technical Information Center (DTIC) · Cited by 96 · see citing works
Shared Situational Awareness in Emergency Management Mitigation and Response
Harrald, J. R., & Jefferson, T. I. (2007) · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.1109/hicss.2007.481 · Cited by 94 · see citing works
Situational Awareness in Complex Systems
Gilson, R. D., Hitchcock, L., Pew, R. A., et al. (1994) · doi:10.21236/ada281448 · Cited by 85 · see citing works
Mental models: a robust definition
Rook, L. (2013) · The Learning Organization · doi:10.1108/09696471311288519 · Cited by 81 · see citing works
Repertoires of collaboration for common operating pictures of disasters and extreme events
Bunker, D., Levine, L., & Woody, C. (2014) · Information Systems Frontiers · doi:10.1007/s10796-014-9515-4 · Cited by 46 · see citing works
Self-citationGuest Editor's Introduction: Toward an Archaeogenealogy of Post-truth
Biesecker, B. A. (2018) · Philosophy and Rhetoric · doi:10.5325/philrhet.51.4.0329 · Cited by 25 · see citing works
Mirbabaie, M., Bunker, D., Stieglitz, S., & Deubel, A. (2019) · Information Systems Frontiers · doi:10.1007/s10796-019-09917-x · Cited by 25 · see citing works
Self-citationBunker, D. (2001) · Information Systems Frontiers · doi:10.1023/a:1011443406476 · Cited by 22 · see citing works
Self-citationEhnis, C., & Bunker, D. (2019) · Behaviour and Information Technology · doi:10.1080/0144929x.2019.1621934 · Cited by 18 · see citing works
Self-citationSocially-shared cognition and consensus in small groups
Levine, J. M. (2017) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2017.12.003 · Cited by 16 · see citing works
Social Media, Rumors, and Hurricane Warning Systems in Puerto Rico
Bui, L. (2019) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2019.321 · Cited by 14 · see citing works
Bright ICT: Social Media Analytics for Society and Crisis Management
Bunker, D., Stieglitz, S., Ehnis, C., et al. (2019) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-20671-0_37 · Cited by 10 · see citing works
Self-citationThe Problem With COVID-19 Artificial Intelligence Solutions and How to Fix Them
Smith, G., & Rustagi, I. (2020) · Stanford Social Innovation Review · doi:10.48558/neme-4m86 · Cited by 4 · see citing works
A Kuhnian Analysis of Revolutionary Digital Disruptions
Riemer, K., & Johnston, R. B. (2016) · Research Online (University of Wollongong) · Cited by 2 · see citing works
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Dwivedi, Y. K., Hughes, L., Kar, A. K., Baabdullah, A. M., Grover, P., Abbas, R., Andreini, D., Abumoghli, I., Barlette, Y., Bunker, D., et al. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102456 · Cited by 761 · see citing works
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Self-citationZhang, Y., Suhaimi, N., Yongsatianchot, N., Gaggiano, J. D., Kim, M., Patel, S. A., Sun, Y., Marsella, S., Griffin, J., & Parker, A. G. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501889 · Cited by 37 · see citing works
- Authors
- Bunker, D.
- Affiliations
- The University of Sydney (AU)
- Corresponding author
- Bunker, Deborah
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 55
- Pages
- 102201
- ISSN
- 0268-4012 (ISSN-L)
- PMC
- PMC7402236
- OpenAlex
- W3046527520
- Cited by
- 178
- References
- 31
- Citations by year
- 2026: 8 · 2025: 21 · 2024: 14 · 2023: 29 · 2022: 43 · 2021: 54 · 2020: 9
- FWCI
- 45.15
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- International Journal of Information Management (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- The Sydney eScholarship Repository (The University of Sydney) (submittedVersion)
- Funders
- University of Sydney Business School,
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Communication › Public Relations and Crisis Communication
- Keywords
- shared situational awareness, infodemic, COVID-19 pandemic, misinformation, recommendation algorithms, bots, influencers, platform trust, digital disruption, social media, artificial intelligence, user profiling
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