The Spread of Voting Attitudes in Social Networks.

The Shapley-Shubik power index is a measure of each voters power in the passage or failure of a vote. We extend this measure to graphs and consider a discrete-time process in which voters may change their vote based on the outcome of the previous vote. We use this model to study how voter influence can spread through a network. We find conditions under which a vanishingly small portion of consenting voters can change the votes of the entirety of the network. For a particular family of graphs, this process can be modeled using cellular automata. In particular, we find a connection between this process and the well-studied cellular automata, Rule 90. We use this connection to show that such processes can exhibit arbitrarily-long periodicity.