Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Self Within Cultural Contexts

Self Within Cultural Contexts

Cultural frameworks for understanding the self are often categorized into two broad orientations: individualism and collectivism. These paradigms influence how people define themselves, relate to others, and interpret their social worlds. Each orientation offers distinct perspectives on autonomy, responsibility, and the role of the individual within a community.Individualistic CulturesIn individualistic cultures like North America and Western Europe, identity is understood as autonomous and...

Impact of Groups on Individuals

Impact of Groups on Individuals

Groups play a fundamental role in shaping individual behavior, as they establish norms that guide interactions and decision-making. Social psychology examines how individuals conform to group expectations, often adjusting their attitudes and actions to align with group norms. These norms can be formal, such as workplace policies, or informal, such as unspoken social expectations within a fraternity.Conformity and Social InfluenceConformity arises when individuals modify their behaviors or...

Central Tendency: Analysis

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...

Impact of Individuals on a Group

Impact of Individuals on a Group

In social psychology, the interplay between individuals and groups is a central concern, particularly regarding how individual actions and characteristics influence group processes and outcomes. While much research emphasizes the group's power in shaping individual behavior, it is equally significant to understand how individuals contribute to the functioning, development, and success of groups.Individual Roles in Group Productivity and Decision-MakingIndividuals are not passive participants in...

Impact of Social Context on Individuals

Impact of Social Context on Individuals

Social psychology examines how the real or imagined presence of others influences individuals' thoughts, feelings, and behaviors. A key concept in this field is the role of social context in shaping behavior. The same individual may act differently depending on the social setting, due to the varying expectations and norms associated with each environment. This context-dependent behavior illustrates the influence of social roles, which prescribe appropriate conduct in specific situations.Social...

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.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Crowding controls the scaling of bus frequency with demand.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Dynamics of discovery and the Heaps-Zipf relationship.

Physical review. E·2026

Same author

From lines to networks.

Physical review. E·2026

Same author

Category learning in deep neural networks: Information content and geometry of internal representations.

Physical review. E·2025

Same author

High-resolution gridded CO<sub>2</sub> and pollutant emission data from road traffic in Indian cities.

Scientific data·2025

Same author

Universal Roughness and the Dynamics of Urban Expansion.

Physical review letters·2025

Search research articles

Related Experiment Video

Updated: Jun 13, 2026

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

Published on: August 5, 2016

Disentangling collective trends from local dynamics.

Marc Barthélemy¹, Jean-Pierre Nadal, Henri Berestycki

¹Institut de Physique Théorique, Commissariat à l'Energie Atomique, URA 2306 Centre National de la Recherche Scientifique F11191 Gif-sur-Yvette, France. marc.barthelemy@cea.fr

Proceedings of the National Academy of Sciences of the United States of America

|April 14, 2010

Summary

This study introduces a new method to separate local and global trends in social phenomena time series. The approach reveals how external factors influence crime and obesity rates, showing decreasing local specificity over time.

More Related Videos

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Related Experiment Videos

Last Updated: Jun 13, 2026

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

Published on: August 5, 2016

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

Social dynamics
Time series analysis
Statistical modeling

Background:

Social phenomena like crime and obesity exhibit both collective trends and local variations.
Traditional methods of analyzing local behavior by comparing to global averages can be misleading.
Understanding the interplay between global influences and local specificities is crucial for accurate social analysis.

Purpose of the Study:

To develop a novel method for disentangling local dynamics from global trends in correlated time series.
To provide a more accurate framework for analyzing societal measures beyond simple global averages.
To investigate the drivers of crime and obesity rates by separating external factors from local influences.

Main Methods:

Utilizing an independent component analysis (ICA) approach for time series decomposition.
Applying the method to synthetic data generated from correlated random walkers.
Analyzing real-world data, including crime rates in the US and France, and US obesity rates.

Main Results:

The method successfully separates local and global dynamics in correlated time series.
US crime rates showed significant fluctuations in the mid-70s, with external factors dominating since the 1980s.
External factors have driven US obesity rates since 2000, with diverse state-level dynamics observed despite similar prevalence.

Conclusions:

The proposed ICA-based method offers a robust way to analyze complex social phenomena.
The findings highlight the increasing influence of external factors on societal trends like crime and obesity.
The study underscores the importance of considering distinct local dynamics even when overall prevalence is similar.