How we find overlapping and hierarchical communities in networks
Networks hide groups inside groups and many nodes belong to more than one group, yet that picture is often missed.
A new algorithm looks for tight little clusters first, then builds bigger layers so you can see both overlapping parts and the hierarchical levels at the same time.
It gives a clear map of who belongs where, and how groups nest into one another, making hidden patterns easy to spot.
This approach works on social, biological and tech networks, helping show hidden links that matter.
The method also ranks how well the groups fit together, so you get a sense which parts are strong and which are fuzzy.
Results are simple to read, not full of numbers, and they reveal connections you might miss otherwise, useful for planning, study, or finding influence.
Imagine seeing a city of groups, some overlap like neighborhoods with shared streets, others stacked like towers, now that picture comes alive.
Try it, explore, and you'll notice patterns that before was hiding.
Read article comprehensive review in Paperium.net:
Detect overlapping and hierarchical community structure in networks
🤖 This analysis and review was primarily generated and structured by an AI . The content is provided for informational and quick-review purposes.
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