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

Social Foundations of Self I: Play and Game

Social Foundations of Self I: Play and Game

The development of self in children is deeply rooted in social interactions, mainly through stages of play and structured games. These stages, outlined by sociologist George Herbert Mead, illustrate how children progressively learn to understand and adopt social roles, forming a cohesive sense of self.The Play Stage: Imitation and Simple Role-TakingIn the early years of childhood, the play stage is characterized by imitative behavior, where children engage in role-playing based on familiar...

You might also read

Related Articles

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

Sort by

Same author

Modeling information diffusion in social media: data-driven observations.

Frontiers in big data·2023

Same author

Experimental evaluation of baselines for forecasting social media timeseries.

EPJ data science·2023

Same author

Vaccination trials on hold: malicious and low credibility content on Twitter during the AstraZeneca COVID-19 vaccine development.

Computational and mathematical organization theory·2022

Same author

The optimal window size for analysing longitudinal networks.

Scientific reports·2017

Search research articles

Related Experiment Video

Updated: Nov 14, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Temporal Mobility Networks in Online Gaming.

Essa Alhazmi^1,2, Nazim Choudhury¹, Sameera Horawalavithana¹

¹Computer Science and Engineering, University of South Florida, Tampa, FL, United States.

Frontiers in Big Data

|March 11, 2021

Summary

This summary is machine-generated.

Player mobility between game servers is predictable, driven by in-game interactions, not friendships. This research aids online gaming platform scaling and management.

Keywords:

mobility diffusion mobility networks multiplayers online games online games online social network (OSN) activities

More Related Videos

Transcranial Direct Current Stimulation for Online Gamers

Transcranial Direct Current Stimulation for Online Gamers

Published on: November 9, 2019

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

Related Experiment Videos

Last Updated: Nov 14, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Transcranial Direct Current Stimulation for Online Gamers

Transcranial Direct Current Stimulation for Online Gamers

Published on: November 9, 2019

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

Area of Science:

Computer Science
Game Studies
Network Science

Background:

Online gaming platforms face challenges in scaling and managing player distribution across servers.
Understanding player mobility is crucial for efficient server provisioning, traffic management, and game promotion.

Purpose of the Study:

To characterize and predict player mobility patterns between gaming servers.
To identify key factors influencing player migration between servers in popular online games.

Main Methods:

Data-driven analysis of player movement in Team Fortress 2 and Counter Strike: Global Offensive.
Development of predictive models for player migration growth and pace.
Statistical analysis to determine the influence of in-game interactions and social network data.

Main Results:

Player mobility between gaming servers can be accurately predicted.
The number of in-game interactions is the primary predictor of player migration pace and growth.
Declared friendships within the online social network do not significantly predict mobility patterns.

Conclusions:

In-game player behavior, specifically interaction frequency, is a stronger determinant of server mobility than social connections.
Findings provide actionable insights for optimizing online game server management and player engagement strategies.