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Decomposing social and semantic networks in emerging “big data” research

Overview of attention for article published in Journal of Informetrics, July 2013
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user
facebook
1 Facebook page

Citations

dimensions_citation
85 Dimensions

Readers on

mendeley
192 Mendeley
citeulike
1 CiteULike
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Title
Decomposing social and semantic networks in emerging “big data” research
Published in
Journal of Informetrics, July 2013
DOI 10.1016/j.joi.2013.05.004
Authors

Han Woo Park, Loet Leydesdorff

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 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 1%
South Africa 2 1%
Malaysia 1 <1%
Netherlands 1 <1%
India 1 <1%
Egypt 1 <1%
Serbia 1 <1%
Unknown 183 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 28%
Researcher 25 13%
Student > Master 24 13%
Professor > Associate Professor 17 9%
Student > Doctoral Student 15 8%
Other 41 21%
Unknown 16 8%
Readers by discipline Count As %
Computer Science 69 36%
Social Sciences 31 16%
Business, Management and Accounting 21 11%
Engineering 8 4%
Economics, Econometrics and Finance 8 4%
Other 30 16%
Unknown 25 13%
Attention Score in Context

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 October 2015.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from Journal of Informetrics
#515
of 754 outputs
Outputs of similar age
#126,356
of 206,711 outputs
Outputs of similar age from Journal of Informetrics
#7
of 10 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 754 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.1. This one is in the 28th percentile – i.e., 28% 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 206,711 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.