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Forecasting sustainable development goals scores by 2030 using machine learning models

Overview of attention for article published in Sustainable Development, May 2024
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
1 news outlet
wikipedia
1 Wikipedia page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
23 Mendeley
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Title
Forecasting sustainable development goals scores by 2030 using machine learning models
Published in
Sustainable Development, May 2024
DOI 10.1002/sd.3037
Authors

Kimia Chenary, Omid Pirian Kalat, Ayyoob Sharifi

Timeline

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 17%
Student > Master 2 9%
Lecturer > Senior Lecturer 2 9%
Student > Ph. D. Student 2 9%
Student > Bachelor 1 4%
Other 3 13%
Unknown 9 39%
Readers by discipline Count As %
Unspecified 4 17%
Business, Management and Accounting 2 9%
Social Sciences 2 9%
Engineering 2 9%
Psychology 1 4%
Other 3 13%
Unknown 9 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 June 2024.
All research outputs
#3,547,547
of 26,108,988 outputs
Outputs from Sustainable Development
#73
of 543 outputs
Outputs of similar age
#32,462
of 238,906 outputs
Outputs of similar age from Sustainable Development
#1
of 14 outputs
Altmetric has tracked 26,108,988 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 543 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 86% 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 238,906 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 14 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 92% of its contemporaries.