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Economies are instances of complex socio-technical systems that are shaped bythe interactions of large numbers of individuals. The individual behavior anddecision-making of consumer agents is determined by complex psychologicaldynamics that include their own assessment of present and future economicconditions as well as those of others, potentially leading to feedback loopsthat affect the macroscopic state of the economic system. We propose that thelarge-scale interactions of a nation's citizens with its online resources canreveal the complex dynamics of their collective psychology, including theirassessment of future system states. Here we introduce a behavioral index ofChinese Consumer Confidence (C3I) that computationally relates large-scaleonline search behavior recorded by Google Trends data to the macroscopicvariable of consumer confidence. Our results indicate that such computationalindices may reveal the components and complex dynamics of consumer psychologyas a collective socio-economic phenomenon, potentially leading to improved andmore refined economic forecasting.

Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics