#Earthquake: Twitter as a Distributed Sensor System
By Andrew T. Crooks, Arie Croitoru, Anthony Stefanidis, Jacek R. Radzikowski. Trans. GIS, 2013
492 citations recorded by the source corpus.
Subfields: Communication, Epidemiology, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/4f6870cdf95ab50df4b155760124cb989ee7814b
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In Communication
In Epidemiology
In Statistical and Nonlinear Physics
Citations in the corpus
- A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management (2015, background): “2010, Crooks et al. 2013), wildfires (De Longueville et al. 2010, Slavkovikj et al. 2014) or disease surveillance (Gomide et al. 2011, Bernardo et al. 2013). However, with such an approach the actual content of social media messages is largely ignored, and with this, much of their potential to impro”
- Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information (2016, background): “Corine land cover [9] or the use of Twitter for determining whether earthquakes were felt [8].”
- Mobile Crowd Sensing and Computing (2015, background): “Crooks et al. [2013] studied the spatial and temporal characteristics of the Twitter feed activity responding to a 5.8-magnitude earth-quake, which could be used to identify and localize the impact area of the earthquake event.”