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Exponential random graph models for little networks

Overview of attention for article published in Social Networks, January 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#30 of 755)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
59 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
67 Mendeley
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Title
Exponential random graph models for little networks
Published in
Social Networks, January 2021
DOI 10.1016/j.socnet.2020.07.005
Authors

George G. Vega Yon, Andrew Slaughter, Kayla de la Haye

Twitter Demographics

The data shown below were collected from the profiles of 59 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 27%
Researcher 11 16%
Student > Master 8 12%
Student > Doctoral Student 4 6%
Student > Bachelor 3 4%
Other 12 18%
Unknown 11 16%
Readers by discipline Count As %
Social Sciences 20 30%
Business, Management and Accounting 6 9%
Agricultural and Biological Sciences 4 6%
Engineering 4 6%
Psychology 3 4%
Other 17 25%
Unknown 13 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 09 February 2022.
All research outputs
#858,968
of 22,703,044 outputs
Outputs from Social Networks
#30
of 755 outputs
Outputs of similar age
#25,402
of 498,374 outputs
Outputs of similar age from Social Networks
#2
of 15 outputs
Altmetric has tracked 22,703,044 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 755 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done particularly well, scoring higher than 96% of its peers.
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 498,374 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.