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Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site

Overview of attention for article published in PLoS ONE, July 2019
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
10 Mendeley
Title
Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site
Published in
PLoS ONE, July 2019
DOI 10.1371/journal.pone.0215266
Authors

Jin-Hui Guo, Tian Guo, Kai-Miao Lin, Dan-Dan Lin, Yu-Fai Leung, Qiu-Hua Chen

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 20%
Student > Master 2 20%
Student > Ph. D. Student 1 10%
Student > Bachelor 1 10%
Student > Postgraduate 1 10%
Other 0 0%
Unknown 3 30%
Readers by discipline Count As %
Environmental Science 2 20%
Business, Management and Accounting 1 10%
Arts and Humanities 1 10%
Agricultural and Biological Sciences 1 10%
Social Sciences 1 10%
Other 0 0%
Unknown 4 40%

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 26 July 2019.
All research outputs
#13,693,836
of 15,519,772 outputs
Outputs from PLoS ONE
#132,521
of 155,335 outputs
Outputs of similar age
#217,878
of 261,040 outputs
Outputs of similar age from PLoS ONE
#117
of 135 outputs
Altmetric has tracked 15,519,772 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 155,335 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.9. This one is in the 1st percentile – i.e., 1% 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 261,040 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.