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Related Concept Videos

Conformity

Conformity

Conformity is the change in a person’s behavior to go along with the group, even if that person does not agree with the group.

Bystander Effect

Bystander Effect

The discussion of bullying highlights the problem of witnesses not intervening to help a victim. This is a common occurrence, as the following well-publicized event demonstrates. In 1964, in Queens, New York, a 19-year-old woman named Kitty Genovese was attacked by a person with a knife near the back entrance to her apartment building and again in the hallway inside her apartment building. When the attack occurred, she screamed for help numerous times and eventually died from her stab wounds.

Milgram's Obedience to Authority

Milgram's Obedience to Authority

Obedience to authority is classically demonstrated in a more famous series of social psychology experiments performed by Stanley Milgram. He was a social psychology professor at Yale who was influenced by the trial of Adolf Eichmann, a Nazi war criminal. Eichmann’s defense for the atrocities he committed was that he was “just following orders.”

Deindividuation

Deindividuation

Deindividuation is a form of social influence on an individual’s behavior such that the individual engages in unusual or non-normal behavior while in a group setting. Why? Because in these group settings, the individual no longer sees themselves as an individual anymore, disinhibiting their behavior and personal restraint.

Social Proof

Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.

Modeling in Therapy

Modeling in Therapy

Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
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Related Experiment Video

Updated: Apr 19, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

Modeling pedestrian's conformity violation behavior: a complex network based approach.

Zhuping Zhou¹, Qizhou Hu¹, Wei Wang²

¹Department of Traffic Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Computational Intelligence and Neuroscience

|December 23, 2014

Summary

Pedestrian conformity violation behaviors at signalized intersections in China were analyzed using complex network concepts. Increased waiting times and spreading rates amplify illegal pedestrian crossings, highlighting network structure

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Related Experiment Videos

Last Updated: Apr 19, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

Traffic Safety
Complex Systems Analysis
Behavioral Science

Background:

Pedestrian injuries and fatalities are a global concern.
Non-compliant pedestrian behaviors at signalized intersections in China contribute to crashes.
Understanding the dynamics of these behaviors is crucial for improving safety.

Purpose of the Study:

To analyze the structural characteristics and evolution of pedestrian conformity violation networks.
To model the spread of illegal pedestrian crossing behavior.
To identify factors influencing pedestrian violation trends.

Main Methods:

Application of complex network concepts and metrics.
Establishment of a pedestrian crossing network and analysis of degree distributions.
Development of a SI model-based spreading model for illegal crossing behavior.
Simulation analysis of behavior trends under varying network structures and spreading rates.

Main Results:

Pedestrian violation crossing behavior increases with longer waiting times after an initial red-light crossing.
Higher spreading rates lead to an increase in pedestrian conformity violation behavior.
Network structure significantly influences the trends of illegal crossing behavior.

Conclusions:

Pedestrian conformity is a key factor in illegal crossings at signalized intersections.
Interventions should consider the impact of waiting times and behavior propagation rates.
Complex network analysis provides valuable insights into pedestrian safety issues.