Network Studies - Modularity

In graph theory and network analysis, modularity measures detect communities or modules in networks. Which of the following statements about modularity is NOT true?

a) Modularity measures the strength of dividing a network into modules or communities. High modularity indicates dense connections within modules and sparse connections between modules.

b) Modularity is a specific measure that can only be applied to undirected, unweighted graphs.

c) Modularity optimization is an approach used to detect communities in networks, but it can potentially lead to resolution issues, especially for larger networks.

d) Modularity values range from -1 to 1. A value of 1 indicates perfectly modular, while a value of 0 indicates no modular structure. Negative modularity can arise when links within modules are less than expected.

e) None of the above.

Original idea by: Leonardo Henrique de Braz.

Comentários

  1. Anônimo4 de junho de 2023 às 07:01

    Interesting question, but (a) is debatable, it depends of the network density as a whole. Alternative (b) is also debatable, since one can introduce weights and direction in the modularity formula. Alternative (d) also has slight problems. There is a tighter interval [-0.5, 1.0] for modularity. All in all, I am not inclined to use this question.

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