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2. Projections Suppose that G is a bipartite graph on a vertex set that is the disjoint union of two sets x and y, where

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2. Projections Suppose that G is a bipartite graph on a vertex set that is the disjoint union of two sets x and y, where each edge connects a verte in X to a vertex in y. The projection of G onto the set x is the graph with vertex set X, where any two elements are joined by an edge whenever they are joined to a common element y EY in the graph G. The adjacency matrix of the projection can be derived from the square A2 of the adjacency matrix A of G. Consider the affilliation network below, with 11 people labelled A to K, and four foci labelled 1, 2, 3 and 4, 6o O O O O O 1. Compute the adjacency matrix of G. 2. Draw the projection on (just) the people, in which two people are joined by an edge if they have a common focus. (Of course, one can do this easily by hand. It would be nice to get networkx to do it for you.) 3. Compute the adjacency matrix B of the projection and compare it to A2. What do you observe? In [ ]: ... text goes here ... 2. Projections Suppose that G is a bipartite graph on a vertex set that is the disjoint union of two sets x and y, where each edge connects a verte in X to a vertex in y. The projection of G onto the set x is the graph with vertex set X, where any two elements are joined by an edge whenever they are joined to a common element y EY in the graph G. The adjacency matrix of the projection can be derived from the square A2 of the adjacency matrix A of G. Consider the affilliation network below, with 11 people labelled A to K, and four foci labelled 1, 2, 3 and 4, 6o O O O O O 1. Compute the adjacency matrix of G. 2. Draw the projection on (just) the people, in which two people are joined by an edge if they have a common focus. (Of course, one can do this easily by hand. It would be nice to get networkx to do it for you.) 3. Compute the adjacency matrix B of the projection and compare it to A2. What do you observe? In [ ]: ... text goes here

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