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Network-based filtering for large email collections in E-Discovery

Overview of attention for article published in Artificial Intelligence and Law, December 2010
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Mentioned by

patent
4 patents

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
25 Mendeley
Title
Network-based filtering for large email collections in E-Discovery
Published in
Artificial Intelligence and Law, December 2010
DOI 10.1007/s10506-010-9099-3
Authors

Hans Henseler

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 4%
Austria 1 4%
Unknown 23 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 32%
Student > Ph. D. Student 6 24%
Student > Doctoral Student 3 12%
Researcher 2 8%
Unspecified 1 4%
Other 2 8%
Unknown 3 12%
Readers by discipline Count As %
Computer Science 9 36%
Economics, Econometrics and Finance 3 12%
Social Sciences 3 12%
Business, Management and Accounting 2 8%
Philosophy 2 8%
Other 3 12%
Unknown 3 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 March 2022.
All research outputs
#7,866,480
of 23,849,058 outputs
Outputs from Artificial Intelligence and Law
#64
of 214 outputs
Outputs of similar age
#56,339
of 186,546 outputs
Outputs of similar age from Artificial Intelligence and Law
#1
of 1 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 214 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 59% 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 186,546 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them