Riskr: a Web2.0 platform to monitor and share disaster information

Farber, Jess, Myers, Trina, Trevathan, Jarrod, Atkinson, Ian, and Andersen, Trevor (2015) Riskr: a Web2.0 platform to monitor and share disaster information. International Journal of Grid and Utility Computing, 6 (2). pp. 98-112.

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Abstract

Disaster management that uses Web-based technology to enhance user collaboration around disasters is an emergent field. A number of dedicated 'disaster portals' exist but do not integrate large social networks such as Twitter and Facebook. These social networking sites can facilitate the analysis and sharing of collective intelligence around disaster information on a far greater scale by increasing accessibility to, and the use of, a disaster portal. This paper presents the 'Riskr' project, which applies a low-technological solution to creating a disaster portal fed by social networking messages. The system has been implemented using Twitter and tested by users to determine the feasibility. Results suggest the combination of online services and interoperability between disaster portals and social networks can further enhance disaster management initiatives as 70.5% of the users were able to estimate the correct location of a disaster (e.g., fallen powerlines, fire, etc).

Item ID: 32310
Item Type: Article (Scholarly Work)
ISSN: 1741-8488
Keywords: Web2.0, disaster management, social networks, cloud computing
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This paper is a revised and expanded version of a paper entitled 'Riskr: a low-technological Web2.0 disaster service to monitor and share information' presented at the '15th International Conference on Network-Based Information Systems (NBiS-2012)', Melbourne, Australia, 26–28 September 2012.

Date Deposited: 16 Aug 2015 22:59
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling @ 25%
08 INFORMATION AND COMPUTING SCIENCES > 0806 Information Systems > 080602 Computer-Human Interaction @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems @ 25%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 100%
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