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The Ambiguous Identifier Clustering Technique

Overview of attention for article published in Electronic Markets, February 2016
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Mentioned by

twitter
1 X user
facebook
1 Facebook page

Citations

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5 Dimensions

Readers on

mendeley
9 Mendeley
Title
The Ambiguous Identifier Clustering Technique
Published in
Electronic Markets, February 2016
DOI 10.1007/s12525-016-0217-2
Authors

Michael Scholz, Markus Franz, Oliver Hinz

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 33%
Professor > Associate Professor 2 22%
Lecturer > Senior Lecturer 1 11%
Researcher 1 11%
Student > Bachelor 1 11%
Other 0 0%
Unknown 1 11%
Readers by discipline Count As %
Business, Management and Accounting 4 44%
Social Sciences 2 22%
Economics, Econometrics and Finance 1 11%
Computer Science 1 11%
Unknown 1 11%
Attention Score in Context

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 09 March 2016.
All research outputs
#17,787,961
of 22,849,304 outputs
Outputs from Electronic Markets
#464
of 568 outputs
Outputs of similar age
#273,779
of 400,824 outputs
Outputs of similar age from Electronic Markets
#9
of 10 outputs
Altmetric has tracked 22,849,304 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 568 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 7th percentile – i.e., 7% 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 400,824 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one.