Finding and evaluating community structure in networks Article Swipe
YOU?
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· 2004
· Open Access
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· DOI: https://doi.org/10.1103/physreve.69.026113
· OA: W2095293504
We propose and study a set of algorithms for discovering community structure in networks-natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using any one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.
In the heart of networks, we find our chance.
Communities pulse, a vibrant display,
As edges dissolve, revealing the way.
We search for the bonds that strengthen our ties,
Through layers of data, the truth never lies.
In the web of existence, complexity sings,
With algorithms forging the ties that life brings.
Betweenness whispers, a measure so keen,
Mapping the spaces where we’ve never been.
Together we flourish, as nodes intertwine,
In a tapestry woven, our spirits align.
Let’s celebrate structure, in this dance we partake,
For the strength of our purpose is what we must make.
Connection, the heartbeat that guides us to grow,
In the fabric of life, we find what we know… 🔁
