Eigenvector Centrality Calculations

[@owaisahussain]

I've downvoted like many others and the reason is that your title says "Eigenvector centrality calculations", which confuses the viewer. I thought you were going to perform the calculations, not how to calculate on Gephi tool. I'm quite positive this was an innocent mistake but please change the title to something more accurate if possible.

[@АнастасияПантелеева-ь7й]

thanks for video. I would like to know how can I calculate the same for bigger amount of nodes, like n=69 nodes and m=84 edges?

[@mosiurr3461]

the adjacency matrix is not correct for the directed network

[@AAA891216]

This video is clear and straight. Thank you so much!

[@blueskye7988]

Hello, please tell me what software you used؟

[@andigao9031]

thanks you .And q1 igenvector centrality is mean the lamada1 corresponding eigenvector?

[@AlanShawesq]

Andi Gao, I don’t understand your question. The Lambda values are the corresponding Eigen values.

[@jareddevedelicana930]

Hello good day sir. Thank you for your video. I have a request here. Maybe you can explain what does it mean when you have an eigenvector value equal to one?

[@beginnerpython6183]

great simple and informative video. I cannot understand why 'dislikes' are same as 'likes'. Thank you for offering useful information.

[@Ayushk11]

cause he did not explained the theory, just shared a website to calculate

[@badaralam9845]

where is link sir?

[@AlanShawesq]

Hi Badar, You can find more information here: www.strategic-planet.com/2019/07/understanding-the-concepts-of-eigenvector-centrality-and-pagerank/

[@sonerseckiner7206]

He confuses eigenvectors with an eigenvector and eigenvalues with an eigenvalue. He even did not know which vector corresponds to which eigenvalue. The answer is simple. The software calculates the eigenvector corresponding to the highest eigenvalue and called it eigenvector centrality.