Revealing Social Group Long-Term Survival for Smart Cities Based on Behavior Graph Structures Using Virtual Game | IEEE Journals & Magazine | IEEE Xplore

Revealing Social Group Long-Term Survival for Smart Cities Based on Behavior Graph Structures Using Virtual Game


Abstract:

With the transformation of human life into virtual worlds based on the reality, current researches of smart cities and sustainability should integrate the factors of virt...Show More

Abstract:

With the transformation of human life into virtual worlds based on the reality, current researches of smart cities and sustainability should integrate the factors of virtual social behaviors. Virtual games are an ideal domain and tools for exploring social science. Therefore, our work innovatively using Nova Empire as a case study to reveal the social group long-term survival via complexity analysis of behavior graph structural properties for building smart cities. Specifically, behavioral data of 101424 players and 5324 alliances from September 2021 to February 2022 are used. Our observations show that the phenomenon of “gap of wealth” in real society also exists in the virtual game. Meanwhile, the player online time is significantly positive related to alliance survival time, which is the foundation of our work. Then, correlation and regression analysis are performed to understand the significance of different structural properties on alliance survival time. Our original findings demonstrate that larger alliance, more subgroups, balanced player distribution, and frequent behavioral interactions will promote long-term survival of the alliance. Small subgroup and a relaxed social environment can improve player online time. Furthermore, we transfer the conclusions from virtual game to real society based on the mapping principle. Finally, new virtual tools and solutions for policymakers to improve smart cities and sustainable society ecosystem, and operation strategies for game designers to improve players retention rate are proposed.
Published in: IEEE Internet of Things Journal ( Volume: 10, Issue: 21, 01 November 2023)
Page(s): 18733 - 18744
Date of Publication: 29 May 2023

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