Computational Assignment 1
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Save each of the following networks in the computer memory as an adjacency matrix, and then write a code to compute the degree of each vertex using the adjacency matrix.
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The files lesmis.dat and polbooks.dat contain a list of edges for two networks. Write a code which constructs adjacency matrices using these edge lists as inputs, and then compute the following for these networks: (a) Average degre and density (b) Local clustering coefficients (c) Degree distribution (d) Matrix of vertex similarities (Cosine and Katz)
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Read the adjacency matrix of a directed network from the file celegans.dat, and write a code to compute the following: (a) Cocitation and bibliographic coupling matrices (b) Eigenvector centralities of the vertices (c) Pagerank centralities of the vertices
Computational Assignment 2 -
Write a code that computes the global clustering coefficient and the degree assortativity of a given network. Using this code, compute these quantifiers for the networks lesmis.dat and polbooks.dat
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Implement the breadth-first search using naive as well as the efficient algorithm. Use these implementations to calculate the distances between all vertex pairs in the network lesmis.dat. Report the actual computation times for the two implementations on your machine.
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Extend the breadth first search so that it finds at least one shortest path between given two vertices. For the network polbooks.dat, compute a shortest path between every vertex pair.
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Implement the two source BFS (Optional)
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Write a code to calculate the betweenness centrality of vertices in an undirected network. Using this code, compute the centrality values of vertices in lesmis.dat (Optional)
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Implement Dijkstra’s algorithm to calculate the shortest distances in a weighted undirected network. Read the network from adjnoun.dat and compute the shortest distances from vertex 0 using this implementation. The network is given in the form of an edge list, and the third column lists edge weights. (Optional)
