Forcing confidence: a Process Tracing approach with a dynamical systems model

Mathematics > Dynamical Systems [Submitted on 16 Jun 2026] Title:Forcing confidence: a Process Tracing approach with a dynamical systems model View PDF HTML (experimental)Abstract:We propose a continuous time dynamical system model for tracing the evolution of confidence in a small decision making group by consensus with the possibility that a forcing factor is exerted onto the confidence of the participants. We experimentally check whether a forcing factor appears, where it begins and ends and how it affects the evolution. We find that the equilibrium value of the confidence is lower in the model with the forcing factor than without it, and that the forcing factor can be identified and induces additional oscillations of the confidence level. This is probably one of the first times when a mathematical model is able to speak about visible effects on the confidence process tracing under alterations of its levels. Pragmatically we find a model that captures influence of participants' confidence level by observing oscillations and equilibrium and we experimentally test it with measures of individual "confidence that the decision is correct" throughout the group decision-making. Submission history From: Aurelian Gheondea [view email][v1] Tue, 16 Jun 2026 12:52:26 UTC (1,608 KB) References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.