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Neminem laedere. An evolutionary agent-based model of the interplay between punishment and damaging behaviours

Overview of attention for article published in Artificial Intelligence & Law, June 2013
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Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
14 Mendeley
Title
Neminem laedere. An evolutionary agent-based model of the interplay between punishment and damaging behaviours
Published in
Artificial Intelligence & Law, June 2013
DOI 10.1007/s10506-013-9146-y
Authors

Nicola Lettieri, Domenico Parisi

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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 36%
Researcher 3 21%
Student > Ph. D. Student 2 14%
Other 1 7%
Student > Bachelor 1 7%
Other 2 14%
Readers by discipline Count As %
Social Sciences 7 50%
Computer Science 3 21%
Business, Management and Accounting 1 7%
Economics, Econometrics and Finance 1 7%
Energy 1 7%
Other 1 7%

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 22 June 2013.
All research outputs
#4,615,237
of 6,241,151 outputs
Outputs from Artificial Intelligence & Law
#43
of 68 outputs
Outputs of similar age
#67,362
of 99,300 outputs
Outputs of similar age from Artificial Intelligence & Law
#2
of 2 outputs
Altmetric has tracked 6,241,151 research outputs across all sources so far. This one is in the 15th percentile – i.e., 15% of other outputs scored the same or lower than it.
So far Altmetric has tracked 68 research outputs from this source. They receive a mean Attention Score of 1.5. This one is in the 1st percentile – i.e., 1% 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 99,300 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.