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A framework for Big Data driven product lifecycle management

Overview of attention for article published in Journal of Cleaner Production, May 2017
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
104 Mendeley
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Title
A framework for Big Data driven product lifecycle management
Published in
Journal of Cleaner Production, May 2017
DOI 10.1016/j.jclepro.2017.04.172
Authors

Yingfeng Zhang, Shan Ren, Yang Liu, Tomohiko Sakao, Donald Huisingh

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 29%
Student > Master 22 21%
Unspecified 14 13%
Student > Bachelor 10 10%
Researcher 9 9%
Other 19 18%
Readers by discipline Count As %
Engineering 34 33%
Unspecified 26 25%
Business, Management and Accounting 17 16%
Computer Science 16 15%
Environmental Science 2 2%
Other 9 9%

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 12 May 2017.
All research outputs
#5,630,492
of 9,896,588 outputs
Outputs from Journal of Cleaner Production
#1,110
of 1,875 outputs
Outputs of similar age
#147,478
of 263,871 outputs
Outputs of similar age from Journal of Cleaner Production
#49
of 95 outputs
Altmetric has tracked 9,896,588 research outputs across all sources so far. This one is in the 26th percentile – i.e., 26% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,875 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 18th percentile – i.e., 18% 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 263,871 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.