Rapid Information Flows and Emergent Political Phenomena: a Complex Systems Theoretic Approach

This research is directed toward understanding the emergence of popular political phenomena under conditions of rapid information propagation (i.e., of the kind facilitated by information and communication technology utilization). Where earlier work on the emergence of popular political phenomena applied agent-based approaches, the work described here draws on work by Sornette et al which was directed toward characterizing an observable signal in the behavior of financial market indices in advance of a market crash. Sornette’s market index model is characterized by a log-periodic power law (LPPL) signal, which captures pre-crash financial market index behaviors per ‘discrete scale invariance,’ a fundamental property of complex adaptive systems. Sornette identified this log-periodic power law behavior following similar work on the characteristics of catastrophic failures in rocket engine components. Sornette speculates about the applicability of LPPL models to the study of socio-political phenomena; the work described here aims to test this applicability. ‘Emergence’ may be constructed as the rapid propagation of protest behavior across a population, representing the revelation of formerly ‘falsified’ political preferences.