Notes based on a version on arxiv, so may not be identical to the journal version

- Betweeness as a measure of centrality is normally calculated as the ratio of shortest paths that go through a node
- Here they use a similar measure but don’t only consider shortest paths (although they give more weight to them)
- Measure here is based on random walks
- Closeness is defined as the mean shortest-path distance from a given node to all other nodes
- Betweeness, on the other hand, is the measure of how often a node lies on a path between other pairs of nodes
- If you consider only shortest paths, some strange behavior can arise in pathologic networks. Also, in the real world, it is likely that not all actions/paths are optimal (such as the letter chains in Milgrams experiments)
- Therefore, value in considering paths of different lenghts, but weighing shorter paths more strongly

- Another proposal is based on max-flow <I don’t know much about network flow> O(m^2 n) <but whats m and n?>
- But using flow can be just as problematic as shortest paths <ok, everything can be problematic but saying other things has problems doesn’t mean whats proposed here doesn’t>
- Here, random walk betweeness is considered <I would definitely says this is more problematic than the other ones>
- This is O((m+n)n^2)
- Mention something called Bonachich’s
*power centrality* which is a discounted measure of centrality
- <Ok, think I got the point – if I need to come back to this paper I can.>

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