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Computational Modeling of Human Social Intelligence and Communication

Authors
Jeungmin Lee
Korea Advanced Institute of Science and Technology (KAIST)
Dr. Jerald D. Kralik
Korea Advanced Institute of Science and Technology (KAIST) ~ Bio and Brain Engineering
Jaeseung Jeong
Korea Advanced Institute of Science and Technology (KAIST), Korea, Republic of (South Korea)
Abstract

The next level in understanding human social cognition is to model it comprehensively. To this end, we have been developing a framework and model that takes as input an event involving someone (focusing on who it was and what they did), and assesses the event based on whether it should change social accounting among individuals, and whether something should be done, such as communicating with others. Here, we present development of the model computationally and results generated by it as predictions to be tested empirically: e.g., more communication about those socially close to us when their actions are positive, and more about those with higher status (i.e., celebrities) when negative; and the relative merit or egregiousness of a wide range of behavior. Leveraging what is known of the human social mind and brain, our work aims to provide a comprehensive model of human social cognition.

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Cite this as:

Lee, J., Kralik, J., & Jeong, J. (2020, July). Computational Modeling of Human Social Intelligence and Communication. Paper presented at Virtual MathPsych/ICCM 2020. Via mathpsych.org/presentation/149.