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Modelling the effect of religion on human empathy based on an adaptive temporal–causal network model

Overview of attention for article published in Computational Social Networks, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)

Mentioned by

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9 X users

Citations

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36 Mendeley
Title
Modelling the effect of religion on human empathy based on an adaptive temporal–causal network model
Published in
Computational Social Networks, January 2018
DOI 10.1186/s40649-017-0049-z
Pubmed ID
Authors

Laila van Ments, Peter Roelofsma, Jan Treur

Abstract

Religion is a central aspect of many individuals' lives around the world, and its influence on human behaviour has been extensively studied from many different perspectives. The current study integrates a number of these perspectives into one adaptive temporal-causal network model describing the mental states involved, their mutual relations, and the adaptation of some of these relations over time due to learning. By first developing a conceptual representation of a network model based on the literature, and then formalizing this model into a numerical representation, simulations can be done for almost any kind of religion and person, showing different behaviours for persons with different religious backgrounds and characters. The focus was mainly on the influence of religion on human empathy and dis-empathy, a topic very relevant today. The developed model could be valuable for many uses, involving support for a better understanding, and even prediction, of the behaviour of religious individuals. It is illustrated for a number of different scenarios based on different characteristics of the persons and of the religion.

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X Demographics

The data shown below were collected from the profiles of 9 X users 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 25%
Student > Master 7 19%
Lecturer 3 8%
Researcher 2 6%
Student > Bachelor 2 6%
Other 3 8%
Unknown 10 28%
Readers by discipline Count As %
Psychology 6 17%
Business, Management and Accounting 3 8%
Arts and Humanities 3 8%
Social Sciences 3 8%
Computer Science 2 6%
Other 9 25%
Unknown 10 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 23 January 2024.
All research outputs
#4,200,686
of 25,450,869 outputs
Outputs from Computational Social Networks
#7
of 41 outputs
Outputs of similar age
#84,264
of 450,085 outputs
Outputs of similar age from Computational Social Networks
#1
of 2 outputs
Altmetric has tracked 25,450,869 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 41 research outputs from this source. They receive a mean Attention Score of 3.8. This one scored the same or higher as 34 of them.
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 450,085 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
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. This one has scored higher than all of them