Quasi-critical dynamics in large-scale social systems regulated by sudden events

Author:

Guo Peng12,Xu Yunhui12ORCID,Guo Shichun12,Tian Yang345ORCID,Sun Pei34

Affiliation:

1. Department of Psychological and Cognitive Sciences, Tsinghua University 1 , Beijing 100084, China

2. Tsinghua Laboratory of Brain and Intelligence, Tsinghua University 2 , Beijing 100084, China

3. Laboratory of Computational Biology and Complex Systems, City University of Macau 3 , Macau 999078, China

4. Faculty of Health and Wellness, City University of Macau 4 , Macau 999078, China

5. Faculty of Data Science, City University of Macau 5 , Macau 999078, China

Abstract

How do heterogeneous individual behaviors arise in response to sudden events and how do they shape large-scale social dynamics? Based on a five-year naturalistic observation of individual purchasing behaviors, we extract the long-term consumption dynamics of diverse commodities from approximately 2.2 million purchase orders. We subdivide the consumption dynamics into trend, seasonal, and random components and analyze them using a renormalization group. We discover that the coronavirus pandemic, a sudden event acting on the social system, regulates the scaling and criticality of consumption dynamics. On a large time scale, the long-term dynamics of the system, regardless of arising from trend, seasonal, or random individual behaviors, is pushed toward a quasi-critical region between independent (i.e., the consumption behaviors of different commodities are irrelevant) and correlated (i.e., the consumption behaviors of different commodities are interrelated) phases as the pandemic erupts. On a small time scale, short-term consumption dynamics exhibits more diverse responses to the pandemic. While the trend and random behaviors of individuals are driven to quasi-criticality and exhibit scale-invariance as the pandemic breaks out, seasonal behaviors are more robust against regulations. Overall, these discoveries provide insights into how quasi-critical macroscopic dynamics emerges in heterogeneous social systems to enhance system reactivity to sudden events while there may exist specific system components maintaining robustness as a reflection of system stability.

Funder

Artificial and General Intelligence Research Program of Guo Qiang Research Institute at Tsinghua University

Tsinghua University Initiative Scientific Research Program

Publisher

AIP Publishing

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