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Real-Time Corporate Carbon Footprint Estimation Methodology Based on Appliance Identification

Overview of attention for article published in IEEE Transactions on Industrial Informatics, February 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
15 Mendeley
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Title
Real-Time Corporate Carbon Footprint Estimation Methodology Based on Appliance Identification
Published in
IEEE Transactions on Industrial Informatics, February 2022
DOI 10.1109/tii.2022.3154467
Authors

Guolong Liu, Jinjie Liu, Junhua Zhao, Jing Qiu, Yiru Mao, Zhanxin Wu, Fushuan Wen

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Unspecified 1 7%
Lecturer > Senior Lecturer 1 7%
Professor 1 7%
Lecturer 1 7%
Other 2 13%
Unknown 7 47%
Readers by discipline Count As %
Computer Science 4 27%
Unspecified 1 7%
Agricultural and Biological Sciences 1 7%
Energy 1 7%
Engineering 1 7%
Other 0 0%
Unknown 7 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 25 June 2022.
All research outputs
#4,840,893
of 25,392,582 outputs
Outputs from IEEE Transactions on Industrial Informatics
#75
of 874 outputs
Outputs of similar age
#108,195
of 451,137 outputs
Outputs of similar age from IEEE Transactions on Industrial Informatics
#3
of 25 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 874 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 90% 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 451,137 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 74% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.