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Mapping the data shadows of Hurricane Sandy: Uncovering the sociospatial dimensions of ‘big data’
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“data-driven public policies may only succeed in economically advantaged, urban, and data-rich areas (Hecht and Stephens, 2014; Shelton et al., 2014), if efforts are not made to improve data collection elsewhere”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Shelton et al., 2014
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Research works printed but not linked: 1
- Red Cross, n.d. The American Red Cross and Dell Launch First-Of-Its-Kind Social Media Digital Operations Center for Humanitarian Relief. <http://www.redcross.org/news/press-release/The-American-Red-Cross-and-Dell-Launch-First-Of-Its-Kind-Social-Media-Digital-Operations-Center-for-Humanitarian-Relief>.
Cited by
Sorted by citations
Digital turn, digital geographies?
Ash, J., Kitchin, R., & Leszczynski, A. (2016) · Progress in Human Geography · doi:10.1177/0309132516664800 · Cited by 772
“…cast a far larger Twitter ‘data shadow’ than the most severely affected, more socioeconomically deprived areas of the tri-state coastline, giving the impression that Manhattan was more deserving of an earlier and/or more concentrated emergency response than was merited (Shelton et al ., 2014).”
BackgroundSocial Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763
“For example, data-driven public policies may only succeed in economically advantaged, urban, and data-rich areas (Hecht and Stephens, 2014; Shelton et al., 2014), if efforts are not made to improve data collection elsewhere (see the “digital divide” on section 9.4).”
BackgroundInfluentialThe role of Big Data in explaining disaster resilience in supply chains for sustainability
Παπαδόπουλος, Θ., Gunasekaran, A., Dubey, R., Nezih Altay, A., Childe, S. J., & Wamba, S. F. (2016) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.03.059 · Cited by 669
“…of the role of Big Data for sustainability and resilience, and more importantly, are studies looking at Big Data and disaster management (Chae et al., 2014; Shelton et al., 2014), there have studies that utilize Big Data (unstructured data) to explain disaster resilience for sustainability.”
InfluentialApplications of artificial intelligence for disaster management
Sun, W., Bocchini, P., & Davison, B. D. (2020) · Natural Hazards · doi:10.1007/s11069-020-04124-3 · Cited by 491
“When assessing the disaster-induced impact on human, sentiment analyses of social media data can track human activity pattern throughout the recovery (Caragea et al. 2014; Hasan and Ukkusuri 2014; Shelton et al. 2014; Resch et al. 2018; Liu et al. 2019b).”
BackgroundShelton, T., Poorthuis, A., & Zook, M. (2015) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2015.02.020 · Cited by 414
Self-citation
Metadata
- Authors
- Shelton, T., Poorthuis, A., Graham, M., & Zook, M.
- Affiliations
- Clark University (US)
- University of Kentucky (US)
- University of Oxford (GB)
- Corresponding author
- Shelton, Taylor
- Venue
- Geoforum
- Publisher
- Elsevier BV
- Published
- 2014-03
- Volume
- 52
- Pages
- 167-179
- ISSN
- 0016-7185 (ISSN-L)
- OpenAlex
- W2062751763
- Cited by
- 256
- References
- 48
- Citations by year
- 2026: 9 · 2025: 13 · 2024: 16 · 2023: 15 · 2022: 14 · 2021: 28 · 2020: 28 · 2019: 31 · 2018: 23 · 2017: 27 · 2016: 23 · 2015: 21 · 2014: 7
- FWCI
- 170.34
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- Geoforum (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Topics
- Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Keywords
- Hurricane Sandy, big data, Twitter, social media, georeferenced records, spatiality, New York metropolitan area, disaster response
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