The final step to this experiment is to recommend users, based on how many friends they share. As mentioned previously, our logic is that, if two users have the same friends, they are highly similar. We could recommend one user to the other on this basis.
We are therefore going to take our existing graph (which has edges relating to friendship) and create a new graph from its information. The nodes are still users, but the edges are going to be weighted edges. A weighted edge is simply an edge with a weight property. The logic is that a higher weight indicates more similarity between the two nodes than a lower weight. This is context-dependent. If the weights represent distance, then the lower weights indicate ...
