A Cognitively Grounded Bayesian Framework for Misinformation Susceptibility
📰 ArXiv cs.AI
Learn how to model misinformation susceptibility using a cognitively grounded Bayesian framework and apply it to real-world scenarios
Action Steps
- Apply the Bounded Pragmatic Listener (BPL) framework to a dataset of social media posts to identify susceptible individuals
- Configure the recursion depth bound and prior compression parameter to capture working memory limits and informativeness
- Test the BPL framework using Bayesian inference to estimate the probability of misinformation susceptibility
- Compare the results with existing models to evaluate the effectiveness of the BPL framework
- Run simulations to analyze the impact of different parameters on misinformation susceptibility
Who Needs to Know This
Data scientists and AI researchers can benefit from this framework to better understand and mitigate the spread of misinformation, while policymakers can use it to inform their decisions
Key Insight
💡 A cognitively grounded Bayesian framework can help model and predict misinformation susceptibility by incorporating bounds on working memory and informativeness
Share This
🚨 New framework alert! 🚨 Bounded Pragmatic Listener (BPL) uses Bayesian inference to model misinformation susceptibility #misinformation #bayesian
Key Takeaways
Learn how to model misinformation susceptibility using a cognitively grounded Bayesian framework and apply it to real-world scenarios
Full Article
Title: A Cognitively Grounded Bayesian Framework for Misinformation Susceptibility
Abstract:
arXiv:2605.09483v1 Announce Type: cross Abstract: In this (work in progress) paper, we present Bounded Pragmatic Listener (or BPL), a cognitively grounded Bayesian framework for modelling susceptibility to information disorder. BPL extends Rational Speech Act theory with three cognitively motivated bounds derived from the bounded rationality literature with a) a recursion depth bound (that emphasises working memory limits);b) a prior compression parameter (which is oriented at capturing informat
Abstract:
arXiv:2605.09483v1 Announce Type: cross Abstract: In this (work in progress) paper, we present Bounded Pragmatic Listener (or BPL), a cognitively grounded Bayesian framework for modelling susceptibility to information disorder. BPL extends Rational Speech Act theory with three cognitively motivated bounds derived from the bounded rationality literature with a) a recursion depth bound (that emphasises working memory limits);b) a prior compression parameter (which is oriented at capturing informat
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