In this paper by Kempe-Kleinberg-Tardos, the Authors propose a greedy algorithms based on submodular functions to determine the $k$ most influential nodes in a graph, with applications to social networks. Basically the algorithm goes as follows:$S = {\rm empty~set}$pick the node with highest individual influence, call it $v_1$; $S = S\cup v_1$remove $v_1$ and all edges connecting $v_1$ to the rest of the networkrepeat until $S$ has $k$ verticesI have two questions about influential nodes in social networks.a) Is there any algorithm to find the solution, or an approximation of it in a decentralized fashion?b) Did anyone apply other algorithms, such as Page-Rank and similar, to solve the same problem?
Decentralized algorithm for determining influential nodes in social networks
ds.algorithms;graph theory;dc.distributed comp;social sciences;heuristics