# Community Detection based on Eigencentrality and Degree Centrality

**URL:** <https://igraph.discourse.group/t/community-detection-based-on-eigencentrality-and-degree-centrality/1353>\
**Category:** Usage\
**Tags:** R\
**Created:** [9 September 2022 03:12 UTC](https://igraph.discourse.group/t/community-detection-based-on-eigencentrality-and-degree-centrality/1353 "2022-09-09T03:12:03Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Ilhom\_Sadriddinov](https://yyz2.discourse-cdn.com/free1/user_avatar/igraph.discourse.group/ilhom_sadriddinov/32/720_2.png) [@Ilhom\_Sadriddinov](https://igraph.discourse.group/u/Ilhom_Sadriddinov)\
**Post date:** [9 September 2022 03:12 UTC](https://igraph.discourse.group/t/community-detection-based-on-eigencentrality-and-degree-centrality/1353/1 "2022-09-09T03:12:04Z")

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Even though it is not directly related to Igraph usage, I wanted to ask a question about Community detection.  
The first is whether it is possible to detect communities using eigencentrality values. For example, if a vertex v has the highest eigencentrality value then we remove the degree(v) - 1 edge(s) from the graph. (But I am not sure which edges need to be removed) Then we continue the process till we get dendrograms. In this case, I am also unsure where to stop.  
Another is doing community detection based on degree centrality. The process would be quite similar to the former.  
This is just a claim-like question, and I want to know the opinions of the igraph community. Because, I am new to this field, and cannot determine the feasibility of some methods in the application. Could someone give me a piece of advice or materials that I can follow?