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Fig. 2 | Applied Informatics

Fig. 2

From: Community detection based on influence power

Fig. 2

Examples to show how to update PP and decide whether a user retains in the next iteration. Before iteration, we have initial IP of every user depending on their degree directly and we set \(\lambda =1\). In a, d, values between users represent intimate degree. In b, e, values between users represent BI. From ac we can see the red point user has initial IP \(=4\) and PP \(=1.71>0\) after updating, which makes him retain as a potential core. From df, we can see the red point user has initial IP \(=2\) and PP \(=\,-\,1.445<0\) after updating, which means he loses chance to be a core so he will be ignored after this iteration

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