Mapping the Data Shadows of Hurricane Sandy: Uncovering the Sociospatial Dimensions of ‘Big Data’
By Taylor Shelton, Ate Poorthuis, Mark Graham, Matthew Zook. 2014
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Alexandra Olteanu
- Carlos Castillo
- Fernando Diaz
- Momin M. Malik
- Emre Kıcıman
- Shahriar Akter
- Jürgen Pfeffer
- Samuel Fosso Wamba
Citations in the corpus
- Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “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).”
- Big data and disaster management: a systematic review and agenda for future research (2017, background): “The impacts of disaster events can disrupt the progress and developmental efforts of nations, often pushing them many years back (Smith and Matthews, 2015; Huang and Cervone, 2016).”
- Digital turn, digital geographies? (2018, background): “…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).”
- Population Bias in Geotagged Tweets (2015, background): “2014a), • natural disasters, crises, and disaster response (Morstatter et al. 2014; Lin and Margolin 2014; Shelton et al. 2014; Sylvester et al. 2014; Kumar, Hu, and Liu 2014), and”
- Applications of artificial intelligence for disaster management (2020, background): “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).”
- Questioning Big Data: Crowdsourcing crisis data towards an inclusive humanitarian response (2016, background): “…scholarly domains, such as new media studies (e.g., Parks, 2009), critical cartography (e.g., Crampton et al., 2013), geoweb studies (e.g., Burns, 2015; Shelton et al., 2014), spatial technologies (e.g., Elwood, 2007), development studies (Avgerou, 2008) and organization sciences (Leonardi, 2011).”