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Related Experiment Video

Updated: Oct 23, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Energy cost study for controlling complex social networks with conformity behavior.

Hong Chen¹, Ee Hou Yong¹

¹Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371.

Physical Review. E

|August 20, 2021

Summary

This summary is machine-generated.

Controlling complex social systems is more energy-efficient using discrete-time models that capture conformity. Heterogeneous scale-free networks are harder to control, requiring more drivers.

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Area of Science:

Complex systems analysis
Network science
Control theory

Background:

Estimating control effort is crucial for complex systems.
Previous studies used continuous-time linear dynamics, which miss social conformity.
Conformity is prevalent in many social and biological systems.

Purpose of the Study:

To develop a discrete-time model for controlling complex social systems with conformity.
To derive energy cost scaling laws for such systems.
To compare control energy requirements with and without conformity.

Main Methods:

Developed a discrete-time model incorporating conformity.
Derived energy cost scaling laws.
Validated results using numerical simulations on model and real networks.
Compared control energy in systems with and without conformity.

Main Results:

Discrete-time modeling successfully captures conformity in complex systems.
Controlling networked systems with conformity requires less energy.
Heterogeneous scale-free networks are less controllable, needing more minimum drivers.

Conclusions:

Discrete-time models offer a more realistic approach to controlling complex social systems with conformity.
Conformity reduces the energy cost of control in networked systems.
Network structure, like heterogeneity in scale-free networks, impacts controllability.