An IoT-based Framework for Understanding Continuous Social Dynamics in a Face-to-Face and Spatially Situated Environment

• Item type: SIG Technical Reports(1)
• 公開日: 2021-10-11
• タイトル: An IoT-based Framework for Understanding Continuous Social Dynamics in a Face-to-Face and Spatially Situated Environment
• タイトル / 言語: en
• タイトル: An IoT-based Framework for Understanding Continuous Social Dynamics in a Face-to-Face and Spatially Situated Environment
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Graduate School of Informatics, Nagoya University／Presently with Nagoya University
• 著者所属: Graduate School of Informatics, Nagoya University
• 著者所属: Graduate School of Informatics, Nagoya University
• 著者所属(英): en
• 著者所属(英): Graduate School of Informatics, Nagoya University / Presently with Nagoya University
• 著者所属(英): en
• 著者所属(英): Graduate School of Informatics, Nagoya University
• 著者所属(英): en
• 著者所属(英): Graduate School of Informatics, Nagoya University
• 著者名: Zineb, Elhamer; Reiji, Suzuki; Takaya, Arita
• 著者名(英): Zineb, Elhamer; Reiji, Suzuki; Takaya, Arita
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: 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.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: 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.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN10505667
• 書誌情報: 研究報告数理モデル化と問題解決（MPS）; 巻 2021-MPS-135, 号 4, p. 1-6, 発行日 2021-10-11
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-8833
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会