@techreport{oai:ipsj.ixsq.nii.ac.jp:00213263,
 author = {Zineb, Elhamer and Reiji, Suzuki and Takaya, Arita and Zineb, Elhamer and Reiji, Suzuki and Takaya, Arita},
 issue = {4},
 month = {Oct},
 note = {Interactions in human social environments are more continuously changing these days due to the recent progress in social networking services (SNS) in two senses: The temporal continuity in interactions and continuity in the closeness of social relationships. Nishimoto et al. constructed a simple computational model for investigating such continuously changing social relationships termed the Social Particle Swarm (SPS) model [1], showing repeated emergence and collapse of cooperative clusters of individuals. However, it is still not clear how face-to-face interactions can affect such dynamic social behaviors while the issues of COVID-19 clarify that human face-to-face interactions are essential even at the age of SNS. We propose an IoT-based framework for investigating face-to-face interactions which involve real human participants communicating with Raspberry Pi Zero devices through Bluetooth radio signals the strength of which reflects the social closeness between two given participants. The participants can press a button attached to the device to change their interaction strategy between cooperation or defection, and the devices have a screen that displays the current strategy in color, as well as the current accumulated score which is updated in real-time. We can simulate a similar situation to the SPS model in which the participants try to maximize their accumulated payoff by getting closer or away from others through an experimental trial. As a proof of concept, we introduce the whole framework and report that it worked properly as expected by showing two series of experiments. One was mainly to see if the framework can capture the dynamics of the social relationships such as the emergence and collapse of cooperative clusters. The second one compared the results against a web-based and anonymous version of online experiments to see the differences in the behavioral patterns of the participants between the two conditions., Interactions in human social environments are more continuously changing these days due to the recent progress in social networking services (SNS) in two senses: The temporal continuity in interactions and continuity in the closeness of social relationships. Nishimoto et al. constructed a simple computational model for investigating such continuously changing social relationships termed the Social Particle Swarm (SPS) model [1], showing repeated emergence and collapse of cooperative clusters of individuals. However, it is still not clear how face-to-face interactions can affect such dynamic social behaviors while the issues of COVID-19 clarify that human face-to-face interactions are essential even at the age of SNS. We propose an IoT-based framework for investigating face-to-face interactions which involve real human participants communicating with Raspberry Pi Zero devices through Bluetooth radio signals the strength of which reflects the social closeness between two given participants. The participants can press a button attached to the device to change their interaction strategy between cooperation or defection, and the devices have a screen that displays the current strategy in color, as well as the current accumulated score which is updated in real-time. We can simulate a similar situation to the SPS model in which the participants try to maximize their accumulated payoff by getting closer or away from others through an experimental trial. As a proof of concept, we introduce the whole framework and report that it worked properly as expected by showing two series of experiments. One was mainly to see if the framework can capture the dynamics of the social relationships such as the emergence and collapse of cooperative clusters. The second one compared the results against a web-based and anonymous version of online experiments to see the differences in the behavioral patterns of the participants between the two conditions.},
 title = {An IoT-based Framework for Understanding Continuous Social Dynamics in a Face-to-Face and Spatially Situated Environment},
 year = {2021}
}