Link Analysis: Closeness centrality of anodes in a directed and undirected graph

The lecture explains closeness centrality as a type of link analysis. Centrality can be used as a measure to identify the importance of a node. Closeness centrality is a type of calculating centrality based on how close a node is to the other nodes. #closenesscentrality #centrality #linkanalysis #graphtheory #networkanalysis

[@computationallinguistics3734]

Hello viewers, the video on closeness centrality is redone for more clarity and detailed evaluation th-cam.com/video/HRMnyMG7DfA/w-d-xo.html

[@plogghuy]

For those wondering the type is actually the normalised closeness centrality measure ie the closeness centrality divided by the total number of nodes -1. Since the pre normalised centrality is the sum raised to the -1 we get the type on screen

[@anchitagarwal1334]

how is distance from node1 to node4 = 2??

[@computationallinguistics3734]

We first assumed the graph to be undirected. So ignoring the node's directionality, we can reach from node 1 to node 4 minimum in two hops i.e., from node 1 to node 3 and then from node 3 to node 4.

[@francescos7361]

Thanks , for this educational contribution.

[@souravde6116]

While directed graph what is the logic of being taken 100? I did not understand. If there is no connection, it should be zero but not 100.

[@computationallinguistics3734]

If you cannot reach from node A to node B so the distance between them is considered to be infinite. Since, we cannot use infinity in our code and we want to get a numeric value, so we assume a value that is very high. Therefore, the value 100 is used as an alternate value for infinity, which can be any other value.

[@computationallinguistics3734]

Here is another video on the same topic that will be of more help: th-cam.com/video/HRMnyMG7DfA/w-d-xo.html

[@Agrover112]

the distance to reach is basically Infinity , 0 means it's kinda the same node so instead of INF we take a large number, since 1/INF=0 which we want to avoid

[@ragilchelvin6964]

I'm sorry sir, can you tell me about your reference to count it, please ? I will use that for citation of my bachelor thesis Thank you..

[@computationallinguistics3734]

Do you mean the source from where I used these calculations?

[@Samuel-wl4fw]

Great video good work

[@muhammadhamza7033]

There is a path between 4 to 1 (4>3>2>1) and 6 to 1 (6>4>3>2>1). Kindly correct

[@computationallinguistics3734]

The shortest paths are calculated from the reference node to all the other nodes. So if we are calculating it for node 1, we will have to look for the shortest path from node 1 to node 4.

[@vicmurai1033]

Thanks for the tutorial

[@LCW9714]

Excuse me.
May I ask a question?
Do you know where is the source of this equation.
I want to know who is the author of the centrality degree equation, and the name of the paper.
Thank you very much.

[@computationallinguistics3734]

Well, there are many recent works that have mentioned these approaches. In fact, there are many different variants of them. Some have explained their working in text while others have provided equations. But if you want to know the original source where these measures were first introduced, that would be hard to find because these are some of the pioneering works and dates back to the start of the graph theory, the Konigberg bridge problem and euler graph in 1736. Searches on these keywords returned few articles from 1950s but they were in a language, I don't understand.

[@LCW9714]

@@computationallinguistics3734 I am really appreciate for your reply.
Thank you very much, you help me a lot.
Your videos are really clear to understand.
Thank you🙏

[@computationallinguistics3734]

Here is another video on the same topic that will be of more help: th-cam.com/video/HRMnyMG7DfA/w-d-xo.html

[@LCW9714]

@@computationallinguistics3734 thank you very much🙏🙏🙏🙏🙏

[@ericfricke4512]

Great stuff. Thanks!

[@ShubhamKumar-nu8rt]

How n=6 and not 7?

[@rubenbarkoudah3635]

very helpful!