Question about Communities
A group of network scientists is analyzing a large social network to uncover community structures. They are evaluating several theoretical principles and algorithmic strategies to decide which framework better explains the observed patterns. After reviewing the literature, they make the following statements:
I. A community structure should balance internal density and external sparsity; however, a subgraph that maximizes internal density alone may fail to capture community boundaries consistent with the overall network topology.
II. In hierarchical clustering of networks, bottom-up strategies tend to merge nodes with high topological similarity or shared neighbors, while top-down strategies progressively dismantle inter-community links that maintain global connectivity.
III. The distinction between strong and weak communities reflects whether the internal–external link condition must hold for each vertex individually or only on average for the entire subgraph.
IV. Finding all cliques in a large network usually is computationally impractical, since the maximal clique problem is NP-complete.
Which of the statements above are correct?
B) Only II and III are correct.
C) Only I and II are correct.
D) Only I, III, and IV are correct.
E) None of the above.
Boa questão, mas fico na dúvida em relação à afirmação I. Parece correta, mas ela usa termos que não entendo direito. Por exemplo, como saber se uma 'community boundary' é consistente com a 'overall network topology'? Também, a IV parece querer implicar que achar todas as cliques é impraticável porque um certo problema lá é NP-completo. Mas, o minimal clique problem é bem fácil. Será que isto quereria dizer que achar todas as cliques é praticável? Ou, olhando por outro lado. Em grafos completos, o maximal clique problem é bem fácil. Será que isso torna achar todas as cliques praticável? São dúvidas que me ocorrem, e que podem ocorrer ao respondedor típico da questão, creio. Desta forma, prefiro deixá-la fora do blog.
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