Transition between distribution patterns in human dynamics with high activity

Ming Zhao1; Jiani Chen1; Jiasheng Lao1; Yanqing Hu2; Jiarong Xie3

2023-09-12

10.1103/PhysRevResearch.5.033179

PHYSICAL REVIEW RESEARCH   影响因子和分区

2643-1564

Complex interactions among a large number of individuals lead to multiple patterns of collective human behavior. However, the theoretical prediction of pattern transitions has not been empirically confirmed. This is because in previous empirical studies, different patterns were observed in different systems, and the coexistence of multiple patterns in the same system was rarely found. By investigating nearly 10 million messages in 252 QQ groups, we find rich distribution patterns of interevent time for human collective behavior, including the transitions between bimodal distribution, double-power-law distribution, and single-power-law distribution. The model developed in this paper suggests that human physiological rhythms and the high collective activity play key roles in the presentation of the single-power-law distribution. These results enhance the empirical research in the field of human dynamics, and are helpful for understanding many complex socioeconomic phenomena.

EI ; ESCI

英语

其他

National Natural Sci- ence Foundation of China["12065002","12147211"] ; Innovation Project of Guangxi Graduate Ed- ucation[YCSW2022154] ; National Natural Science Foundation of China["12065002","12147211"] ; Innovation Project of Guangxi Graduate Education[YCSW2022154] ; Guangdong Provincial Department of Science and Technology[2020B1515020052] ; Young TopNotch Talents in Technological Innovation[2019TQ05X138]

Physics

Physics, Multidisciplinary

WOS:001141090100002

AMER PHYSICAL SOC

20234014828353

Behavioral research

Ergonomics and Human Factors Engineering:461.4 ; Social Sciences:971

人工提交

1.College of Physical Science and Technology, Guangxi Normal University, Guilin 541004, People’s Republic of China
2.Department of Statistics and Data Science, College of Science, Southern University of Science and Technology, Shenzhen 518055, People’s Republic of China
3.School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, People’s Republic of China

Ming Zhao,Jiani Chen,Jiasheng Lao,et al. Transition between distribution patterns in human dynamics with high activity[J]. PHYSICAL REVIEW RESEARCH,2023,5(3).

Ming Zhao,Jiani Chen,Jiasheng Lao,Yanqing Hu,&Jiarong Xie.(2023).Transition between distribution patterns in human dynamics with high activity.PHYSICAL REVIEW RESEARCH,5(3).

Ming Zhao,et al."Transition between distribution patterns in human dynamics with high activity".PHYSICAL REVIEW RESEARCH 5.3(2023).