Journal
COMPLEX ADAPTIVE SYSTEMS MODELING
Volume 1, Issue -, Pages -Publisher
SPRINGER
DOI: 10.1186/2194-3206-1-9
Keywords
Phase transitions; Mutual information; Transfer entropy; Social networks; Stock markets; Expertise
Funding
- US Air Force [AOARD 104116]
- Australian Research Council [LP0453657, DP0881829]
- Dr Mortimer and Theresa Sackler Foundation
- Australian Research Council [DP0881829, LP0453657] Funding Source: Australian Research Council
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We examine the role of information-based measures in detecting and analysing phase transitions. We contend that phase transitions have a general character, visible in transitions in systems as diverse as classical flocking models, human expertise, and social networks. Information-based measures such as mutual information and transfer entropy are particularly suited to detecting the change in scale and range of coupling in systems that herald a phase transition in progress, but their use is not necessarily straightforward, possessing difficulties in accurate estimation due to limited sample sizes and the complexities of analysing non-stationary time series. These difficulties are surmountable with careful experimental choices. Their effectiveness in revealing unexpected connections between diverse systems makes them a promising tool for future research.
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