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Cumulative Dynamics of Independent Information Spreading Behaviour: A Physical Perspective
Cangqi Zhou1,2, Qianchuan Zhao3,4, Wenbo Lu1,2
1Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing, 100084, China.
Scientific Reports
|July 19, 2017
Summary
This study models information spreading in social networks by comparing it to spin glass systems. It reveals universal power-law rules governing independent user behavior and message propagation dynamics.
Area of Science:
- Complex Systems
- Computational Social Science
- Information Science
Background:
- Online social networks facilitate widespread information dissemination.
- Limited research exists on independent decision-making patterns in information spreading.
- Microblogging platforms share characteristics with disordered spin glass systems.
Purpose of the Study:
- To develop a model for independent information spreading behavior in online social networks.
- To identify universal rules governing information propagation.
- To explore the analogy between microblogging and spin glass systems.
Main Methods:
- Comparison of microblogging data with spin glass systems.
- Adaptation of the Trap Model from spin glass physics.
- Derivation of a power-function model for spreading activity growth.
- Validation using a real-world microblogging dataset.
Main Results:
- Identified analogous relationships between microblogging and spin glass systems.
- Observed aging effects in both systems.
- Developed a unified power-function model incorporating memory, interest dynamics, and message age.
- Validated the model with empirical data.
Conclusions:
- Information spreading follows invariable rules beyond specific network features.
- The derived model accurately captures independent spreading dynamics.
- This approach offers a novel methodology for studying human dynamics and predicting information spread.
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