Information and Phase Transitions in Socio-economic Systems

Terence Bossomaier, Lionel Barnett, Michael Harre

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)
18 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)1-25
Number of pages25
JournalComplex Adaptive Systems Modeling
Issue number1
Publication statusPublished - 2013


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