A big thank you to CoMSES Net for the opportunity to present our “Descriptive Norm and Fraud Dynamics” model as part of the series ‘Ten-Minute Dialogues: Computational Models’.
Our model illustrates how fraudulent behavior can either spread or be contained within non-hierarchical organizations, such as peer networks, through social influence manifested as a descriptive norm. It investigates variations in the descriptive norm mechanism, ranging from locally distorted information to globally accurate knowledge.
The results demonstrate that the same variation in the descriptive norm can produce differing aggregate levels of fraud across various fraud categories. By incorporating two empirically derived norm sensitivity distributions corresponding to distinct fraud categories, the model reveals how these differences influence the overall outcomes.
https://www.youtube.com/watch?v=KGhzCGNNx9s
The model is publicly accessible and can be explored further at:
Alexandra Eckert, Matthias Meyer, Christian Stindt (2025, January 07). “Descriptive Norm and Fraud Dynamics” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://doi.org/10.25937/gqxp-7311
