Transfer entropy between communities in complex networks
Jan Korbel, Xiongfei Jiang, Bo Zheng

TL;DR
This paper uses transfer entropy to analyze information flow between communities in complex networks, demonstrating its effectiveness in capturing nonlinear interactions, with applications to financial markets and rare event transfer analysis.
Contribution
It introduces transfer entropy as a tool for studying community interactions in complex networks, including nonlinear and rare event information transfer, with empirical analysis on financial markets.
Findings
Transfer entropy coherently describes community interactions.
Nonlinear interactions are effectively captured.
Analysis of rare event transfer using Rényi transfer entropy.
Abstract
With the help of transfer entropy, we analyze information flows between communities of complex networks. We show that the transfer entropy provides a coherent description of interactions between communities, including non-linear interactions. To put some flesh on the bare bones, we analyze transfer entropies between communities of five largest financial markets, represented as networks of interacting stocks. Additionally, we discuss information transfer of rare events, which is analyzed by R\'enyi transfer entropy.
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Complex Network Analysis Techniques · Neural Networks and Applications
