  Online social networks offer a new way to investigate financial markets'
dynamics by enabling the large-scale analysis of investors' collective
behavior. We provide empirical evidence that suggests social media and stock
markets have a nonlinear causal relationship. We take advantage of an extensive
data set composed of social media messages related to DJIA index components. By
using information-theoretic measures to cope for possible nonlinear causal
coupling between social media and stock markets systems, we point out stunning
differences in the results with respect to linear coupling. Two main
conclusions are drawn: First, social media significant causality on stocks'
returns are purely nonlinear in most cases; Second, social media dominates the
directional coupling with stock market, an effect not observable within linear
modeling. Results also serve as empirical guidance on model adequacy in the
investigation of sociotechnical and financial systems.
