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Flood modelling for cities using Cloud computing

Overview of attention for article published in Journal of Cloud Computing, March 2013
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Mentioned by

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1 X user

Citations

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53 Dimensions

Readers on

mendeley
102 Mendeley
Title
Flood modelling for cities using Cloud computing
Published in
Journal of Cloud Computing, March 2013
DOI 10.1186/2192-113x-2-7
Authors

Vassilis Glenis, Andrew Stephen McGough, Vedrana Kutija, Chris Kilsby, Simon Woodman

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 1 <1%
Netherlands 1 <1%
Portugal 1 <1%
Unknown 96 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 25%
Student > Master 14 14%
Researcher 8 8%
Professor > Associate Professor 5 5%
Student > Bachelor 5 5%
Other 18 18%
Unknown 26 25%
Readers by discipline Count As %
Engineering 32 31%
Computer Science 16 16%
Environmental Science 11 11%
Earth and Planetary Sciences 5 5%
Social Sciences 3 3%
Other 5 5%
Unknown 30 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 September 2013.
All research outputs
#15,280,625
of 22,723,682 outputs
Outputs from Journal of Cloud Computing
#88
of 254 outputs
Outputs of similar age
#123,660
of 197,468 outputs
Outputs of similar age from Journal of Cloud Computing
#1
of 1 outputs
Altmetric has tracked 22,723,682 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 254 research outputs from this source. They receive a mean Attention Score of 2.0. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 197,468 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them