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The dynamics of information-driven coordination phenomena: A transfer entropy analysis.
Javier Borge-Holthoefer1, Nicola Perra2, Bruno Gonçalves3
1Qatar Computing Research Institute, Hamad Bin Khalifa University, P.O. Box 5825 Doha, Qatar.
Science Advances
|April 7, 2016
Summary
Researchers developed a new method using social media data to detect and understand collective social events. This approach identifies key information transfer changes that signal the start of these phenomena.
Area of Science:
- Social network analysis
- Information theory
- Computational social science
Background:
- Social media data offers novel insights into collective social phenomena dynamics.
- Understanding the emergence and prominence of social events requires robust analytical frameworks.
Purpose of the Study:
- To define and measure temporal and structural signatures of collective social events using an information-theoretic approach.
- To develop a methodology for extracting directed influence networks from social media data.
- To validate the framework through empirical analysis of case studies.
Main Methods:
- Symbolic transfer entropy analysis of microblogging time series.
- Extraction of directed networks of influence among geolocalized social system subunits.
- Identification of changes in information transfer time scales and network structure.
Main Results:
- The methodology successfully captures system-level dynamics near the onset of collective phenomena.
- A change in information transfer time scale was identified, flagging the onset of information-driven events.
- An order-disorder transition in the directed influence network was observed, indicating endogenous drivers.
Conclusions:
- Collective social phenomena can be characterized as endogenous structural transitions within information transfer networks.
- The developed framework aids in defining models and predictive algorithms for analyzing societal events using open-source data.
- This approach provides a quantitative method for understanding the emergence of collective behavior from social media.
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