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Social network data consists of a collection of "nodes" (which can be any sort of entity - e.g. people, corporations) and "links" (which can be any sort of relationship - e.g. friend, sharing a board member).
0
votes
Scalable way to calculate betweenness centrality for a graph in spark
Sorry, I do not think you can compute the exact betweenness centrality of nodes in a graph this size, as its complexity is $O(n\cdot m)$ where $n$ is the number of nodes, $m$ the number of links.
The …
2
votes
Reduce size of a network graph for bipartite projection
I think the problem is not with the data size, but with the presence of large degree nodes (the degree of a node is its number of neighbours).
Indeed all neighbours of a node in the bipartite graph ar …