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Monotonicity of centrality measures

When you add an edge to an undirected network, one of its endpoints can lose rank. We prove that the two can never both lose it, for closeness, betweenness and distance-decay centralities.

A centrality measure scores how important each node of a network is. In a directed network, a new arc is like a new follower: for almost every classical measure it raises the score and the rank of the node it points to. In an undirected network a new edge is like a new friendship, shared by both endpoints, and one would expect both to gain. The figure shows that this can fail. With closeness centrality, another node can gain more from the new edge than one of its endpoints does, and overtake it.

The dashed edge closes a loop. Its right endpoint gets closer to the left of the network, but the ringed node gains more: it gets closer to that endpoint and to all of its leaves at once. It overtakes the endpoint, which drops from 3rd to 4th. Click two nodes that are not linked to try another edge: on most, no node overtakes either endpoint, and on none are both overtaken.

With Paolo Boldi, Flavio Furia and Sebastiano Vigna we introduced a weaker property, semi-monotonicity, which asks only that at least one endpoint is not overtaken by any other node. We proved that closeness, a large class of distance-based centralities and, more surprisingly, betweenness all satisfy it. For the last two we proved a stronger property, basin dominance.

Papers