Computational Model Library

Sensitivity of the Deffuant model to measurement error (1.0.0)

This code can be used to analyze the sensitivity of the Deffuant model to different measurement errors. Specifically to:
- Intrinsic stochastic error
- Binning of the measurement scale
- Random measurement noise
- Psychometric distortions

The script provides graphs for each one of these

Release Notes

First version with the complete analysis of the different type of measurement errors.

Associated Publications

Sensitivity of the Deffuant model to measurement error 1.0.0

Submitted by Dino Carpentras Published Jun 07, 2021 Last modified Jun 07, 2021
Deffuant model opinio dynamics measurement error sensitivity analysis

This code can be used to analyze the sensitivity of the Deffuant model to different measurement errors. Specifically to:
- Intrinsic stochastic error
- Binning of the measurement scale
- Random measurement noise
- Psychometric distortions

The script provides graphs for each one of these

Release Notes

First version with the complete analysis of the different type of measurement errors.

Cite this Model

Dino Carpentras (2021, June 07). “Sensitivity of the Deffuant model to measurement error” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/4a51fbfb-9117-4561-b915-b023fc4b5bdd/releases/1.0.0/

Replication of a previously described model

https://doi.org/10.1142/S0219525900000078

References

Carpentras, Dino, Alejandro Dinkelberg, and Michael Quayle. “A new degree of freedom for opinion dynamics models: the arbitrariness of scales.” arXiv preprint arXiv:2010.04788 (2020).

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Contributors
Dino Carpentras
DOI
No assigned DOI
Model Version
1.0.0
License
CC-BY-NC-4.0
Programming Language
Python
Software Framework
Jupyter Notebook Python
Operating System
Windows
Publish Date
Monday, June 07, 2021
Last Updated
Monday, June 07, 2021
Downloads 33
Peer Review
Unreviewed
Version Submitter First published Last modified Status
1.0.0 Dino Carpentras Mon Jun 7 18:28:25 2021 Mon Jun 7 18:30:13 2021 Published

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