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Modularity affects the robustness of scale-free model and real-world social networks under betweenness and degree-based node attack

Overview of attention for article published in Applied Network Science, November 2021
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About this Attention Score

  • 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
3 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
9 Mendeley
Title
Modularity affects the robustness of scale-free model and real-world social networks under betweenness and degree-based node attack
Published in
Applied Network Science, November 2021
DOI 10.1007/s41109-021-00426-y
Authors

Quang Nguyen, Tuan V. Vu, Hanh-Duyen Dinh, Davide Cassi, Francesco Scotognella, Roberto Alfieri, Michele Bellingeri

Twitter Demographics

The data shown below were collected from the profiles of 3 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 11%
Lecturer 1 11%
Student > Doctoral Student 1 11%
Student > Ph. D. Student 1 11%
Researcher 1 11%
Other 1 11%
Unknown 3 33%
Readers by discipline Count As %
Computer Science 1 11%
Economics, Econometrics and Finance 1 11%
Physics and Astronomy 1 11%
Social Sciences 1 11%
Medicine and Dentistry 1 11%
Other 1 11%
Unknown 3 33%

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 15 November 2021.
All research outputs
#14,219,854
of 21,173,213 outputs
Outputs from Applied Network Science
#325
of 437 outputs
Outputs of similar age
#248,094
of 421,985 outputs
Outputs of similar age from Applied Network Science
#63
of 96 outputs
Altmetric has tracked 21,173,213 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 437 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one is in the 22nd percentile – i.e., 22% 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 421,985 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.