Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
The Journal of Machine Learning Research
On Deception Detection in Multiagent Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Research on deception detection has been mainly focused on two kinds of approaches. In one, people consider deception types and taxonomies, and use different counter strategies to detect and reverse deception. In the other, people search for verbal and non-verbal cues in the content of deceptive communication. However, general theories that study fundamental properties of deception which can be applied in computational models are still very rare. In this work, we propose a general model of deception detection guided by a fundamental principle in the formation of communicative deception. Experimental results using our model demonstrate that deception is distinguishable from unintentional misinformation.