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Diversity of individual mobility patterns and emergence of aggregated scaling laws

Overview of attention for article published in Scientific Reports, September 2013
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Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
110 Dimensions

Readers on

mendeley
117 Mendeley
citeulike
1 CiteULike
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Title
Diversity of individual mobility patterns and emergence of aggregated scaling laws
Published in
Scientific Reports, September 2013
DOI 10.1038/srep02678
Pubmed ID
Authors

Xiao-Yong Yan, Xiao-Pu Han, Bing-Hong Wang, Tao Zhou

Abstract

Uncovering human mobility patterns is of fundamental importance to the understanding of epidemic spreading, urban transportation and other socioeconomic dynamics embodying spatiality and human travel. According to the direct travel diaries of volunteers, we show the absence of scaling properties in the displacement distribution at the individual level,while the aggregated displacement distribution follows a power law with an exponential cutoff. Given the constraint on total travelling cost, this aggregated scaling law can be analytically predicted by the mixture nature of human travel under the principle of maximum entropy. A direct corollary of such theory is that the displacement distribution of a single mode of transportation should follow an exponential law, which also gets supportive evidences in known data. We thus conclude that the travelling cost shapes the displacement distribution at the aggregated level.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
United Kingdom 2 2%
Netherlands 2 2%
Italy 1 <1%
Australia 1 <1%
Malaysia 1 <1%
Spain 1 <1%
Portugal 1 <1%
Unknown 106 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 30%
Researcher 15 13%
Student > Master 14 12%
Professor > Associate Professor 11 9%
Student > Doctoral Student 6 5%
Other 24 21%
Unknown 12 10%
Readers by discipline Count As %
Computer Science 26 22%
Engineering 20 17%
Physics and Astronomy 16 14%
Social Sciences 11 9%
Earth and Planetary Sciences 7 6%
Other 18 15%
Unknown 19 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 24 September 2013.
All research outputs
#10,762,531
of 18,245,787 outputs
Outputs from Scientific Reports
#49,377
of 98,655 outputs
Outputs of similar age
#89,744
of 177,513 outputs
Outputs of similar age from Scientific Reports
#26
of 52 outputs
Altmetric has tracked 18,245,787 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 98,655 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.8. This one is in the 47th percentile – i.e., 47% 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 177,513 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.