Finding related-node clusters I currently have an undirected weighted graph. I am trying to find a good algorithm for learning/finding a cluster of closely related nodes and/or loosely relationship within a cluster in a graph given a size of the cluster. For example, here the longer edges represent the farther relationship between 2 nodes. We identified 2 clusters where each cluster has a close relationship internally. I am new to computer science, could you please suggest an algorithm or a paper for this problem? Your help is really appreciated!
The problem you are trying to solve is called community detection or community structure, where several popular algorithms are listed, such as Girvan–Newman algorithm and Minimum-cut method.

You can find many related questions and answers on this site, on CrossValidate and on StackOverflow, such as the following:


Community detection in weighted directed graphs for fixed number of communities.
How to do community detection in a weighted social network/graph?
What are the differences between community detection algorithms in igraph?


A good introduction can be found at Community detection in graphs.

A recent survey can be found at Community detection in social networks.