I am a beginner in matlab. So, Could anyone please help me to create an adjacency matrix based on this attached dataset? This set consists of nodes and edges, so I want adjacency matrix where 1 represents connected nodes otherwise 0.

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SUNANNA S S 2017-3-21

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评论： SUNANNA S S 2017-3-28

采纳的回答： Guillaume

twitnet.csv

Thanks

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Guillaume 2017-3-24

We know what an adjacency matrix is. Rik was asking you to demonstrate that you'd made some effort towards getting your answer, particularly if it's homework.

SUNANNA S S 2017-3-27

编辑：Guillaume 2017-3-27

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Sorry for the mistake Sir. This is the code that I tried, but this has so many problems.Please help.

function osnToBIS()
clc;
A=csvread('twitnet');
B=unique(A);
m=size(B);
for i=1:size(B)
    [r,c]=find(B(i)==A);
   for j=1:size(c)
        if c(j)==1
           c(j)=2;
        else
           c(j)=1; 
        end
   end
    N=A(r,c);
    radj=find(adj(:,1)==B);
    cadj=find(adj(1,:)==unique(N));
    adj(radj,cadj);
 end

The error in this program is:

Undefined variable adj.
Error in osnToBIS  (line 16)
    radj=find(adj(:,1)==B);

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Guillaume 2017-3-21

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Once you've imported your data, the graph and adjacency function are pretty much all you need . However, considering that you've got 892 nodes, that adjacency matrix is going to be big and imposible to visualise.

Two issues are that your text file contains a lot of empty entries (just ,) which needs to be filtered out, and that if you give numeric nodes to graph it expects these to be numbered from 1 to numberofnoes. You can either converts the numbers to char arrays or renumber the nodes(with unique).

edges = dlmread('twitnet.csv');
edges(all(edges == 0, 2), :) = [];  
edges = arrayfun(@num2str, edges, 'UniformOutput', false);
g = graph(edges(:, 1), edges(:, 2));
plot(g);
adjm = full(adjacency(g))

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Guillaume 2017-3-24

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You really should move to a version of matlab a bit more recent. You're missing out on lots of useful graph functions (in particular, the above will give you a very nice plot of your graph).

Without the nice graph functions, you can still build the adjacency matrix with a bit more effort:

edges = dlmread('twitnet.csv');
edges(all(edges == 0, 2), :) = [];  
[uedges, ~, erow] = unique(edges.', 'stable');  %transpose and stable to give the same output as graph
adjm2 = full(sparse(erow(1:2:end), erow(2:2:end), 1, numel(uedges), numel(uedges)));
adjm2 = adjm2 + adjm2.';