© Springer Nature Switzerland AG 2020. This paper discusses the modeling for interactions between the behaviors of participants in a meeting for decision making. First, we adopt the behaviors (i.e., eye, facial, and hand movements) detected by OpenPose [9] as a skeleton detection algorithm using a single camera. Second, we propose a modeling method for the participant behaviors based on neural networks. Furthermore, we discuss the relationships between the participant behaviors and the model parameters in multi-layered neural networks based on the experimental results. Notably, we show that the participant characteristics are represented by the indices based on the parameters of the abovementioned models.