A Study of Influence Propagation in Social and Financial Networks
Graphs and networks are a crucial tool to model various phenomena in almost every branch of science. This book studies several different problems that are related to networks; the common theme among these problems is that they all describe some kind of an entity or effect that propagates though the network. The first part of the book focuses on majority/minority processes, when the actors in the network prefer to switch to the most/least common state in their neighborhood. These processes can model various situations in practice: they can represent the spreading of political opinions in a social network, the adoption of different social media platforms, the production strategies of rival companies, the frequency selection of devices in a wireless network, and many more. The book present several upper and lower bounds on the stabilization time of these processes in a general network topology. The second part studies financial networks: a system of banks that are interconnected by different kinds of debt contracts. If one of the banks goes bankrupt and cannot pay its liabilities, then this might cause other banks to go bankrupt as well, leading to a ripple effect through the whole system. There are countless interesting questions in this setting that are related to the properties of the underlying network, such as how regulators can enforce certain properties in these systems, how banks can execute different actions to improve their situation, or how the system behaves if default announcements are made in a step-by-step fashion. Finally, we conclude with a brief discussion of pebble games, where the propagation effect that we study is computation itself: the network represents the interdependencies of variables in a complex computational task, and a pebble game models our progress of computing more and more values in this graph until we arrive at the final result. The book assumes that readers have a strong background in theoretical computer science, but it requires no prior knowledge of the discussed network problems or the corresponding application areas.