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<p>This study proposes a simulation framework for the co-evolution process between social networks and activity engagement. The framework features a clear model specification strategy and an algorithm enabling population-wide network inference. Data collection combines social network surveys and activity diaries, allowing for the use of standard statistical modeling methods. The performance of the proposed framework was tested by focusing on how international students expand their social networks after arriving in Japan. Empirical results demonstrate that the proposed framework can effectively trace the growth of students’ social networks. Scenario analysis indicates that restrictions on out-of-home activities would significantly limit social network expansion. Furthermore, we show that network properties such as transitivity can be controlled by (1) increasing tendencies to meet friends of friends, and/or (2) enhancing tie retention with friends of friends. These two strategies are found to have distinctly different impacts on network properties. Overall, our framework offers a robust approach to simulating and analyzing the complex interplay between social networks and activity engagement, with potential applications in various urban and transportation policies.</p>

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A co-evolutionary simulation of social network and activity engagement

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月27日

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  • Makoto Chikaraishi,
  • Noboru Harata,
  • Swarnali Dihingia,
  • Kiyoshi Takami,
  • Giancarlos Parady

摘要

This study proposes a simulation framework for the co-evolution process between social networks and activity engagement. The framework features a clear model specification strategy and an algorithm enabling population-wide network inference. Data collection combines social network surveys and activity diaries, allowing for the use of standard statistical modeling methods. The performance of the proposed framework was tested by focusing on how international students expand their social networks after arriving in Japan. Empirical results demonstrate that the proposed framework can effectively trace the growth of students’ social networks. Scenario analysis indicates that restrictions on out-of-home activities would significantly limit social network expansion. Furthermore, we show that network properties such as transitivity can be controlled by (1) increasing tendencies to meet friends of friends, and/or (2) enhancing tie retention with friends of friends. These two strategies are found to have distinctly different impacts on network properties. Overall, our framework offers a robust approach to simulating and analyzing the complex interplay between social networks and activity engagement, with potential applications in various urban and transportation policies.