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Identifying the source types of the seismic events using discriminant functions and tree-based machine learning algorithms at Soma Region, Turkey

Overview of attention for article published in Environmental Earth Sciences, May 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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5 X users

Readers on

mendeley
3 Mendeley
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Title
Identifying the source types of the seismic events using discriminant functions and tree-based machine learning algorithms at Soma Region, Turkey
Published in
Environmental Earth Sciences, May 2023
DOI 10.1007/s12665-023-10946-8
Authors

Evrim Yavuz, Muzaffer Can Iban, Ercan Arpaz

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Engineering 1 33%
Unknown 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 18 May 2023.
All research outputs
#7,749,702
of 25,466,764 outputs
Outputs from Environmental Earth Sciences
#156
of 1,888 outputs
Outputs of similar age
#126,612
of 391,462 outputs
Outputs of similar age from Environmental Earth Sciences
#4
of 16 outputs
Altmetric has tracked 25,466,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,888 research outputs from this source. They receive a mean Attention Score of 2.0. This one has done particularly well, scoring higher than 91% 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 391,462 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.