Beschreibung:
We study proliferation of an action in binary action network coordination games that are generalized to include global effects. This captures important aspects of proliferation of a particular action or narrative in online social networks, providing a basis to understand their impact on societal outcomes. Our model naturally captures complementarities among starting sets, network resilience, and global effects, and highlights interdependence in channels through which contagion spreads. We present new, natural, computationally tractable, and efficient algorithms to define and compute equilibrium objects that facilitate the general study of contagion in networks and prove their theoretical properties. Our algorithms are easy to implement quantifying relationships previously inaccessible due to computational intractability. We conduct millions of Monte Carlo simulations in scale-free networks with 1,000 players, providing quantitative and qualitative insights. The scope of application is enlarged given the many other situations across different fields that may be modeled using this framework