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A Set-Theoretic Approach to Modeling Network Structure

Department of Computer Science, University of Virginia, Charlottesville, VA 22911, USA
Academic Editor: Lijun Chang
Algorithms 2021, 14(5), 153;
Received: 27 March 2021 / Revised: 27 April 2021 / Accepted: 28 April 2021 / Published: 11 May 2021
(This article belongs to the Special Issue Network Science: Algorithms and Applications)
Three computer algorithms are presented. One reduces a network N to its interior, I. Another counts all the triangles in a network, and the last randomly generates networks similar to N given just its interior I. However, these algorithms are not the usual numeric programs that manipulate a matrix representation of the network; they are set-based. Union and meet are essential binary operators; contained_in is the basic relational comparator. The interior I is shown to have desirable formal properties and to provide an effective way of revealing “communities” in social networks. A series of networks randomly generated from I is compared with the original network, N. View Full-Text
Keywords: interior; reduction; weak links; closure; communities interior; reduction; weak links; closure; communities
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MDPI and ACS Style

Pfaltz, J.L. A Set-Theoretic Approach to Modeling Network Structure. Algorithms 2021, 14, 153.

AMA Style

Pfaltz JL. A Set-Theoretic Approach to Modeling Network Structure. Algorithms. 2021; 14(5):153.

Chicago/Turabian Style

Pfaltz, John L. 2021. "A Set-Theoretic Approach to Modeling Network Structure" Algorithms 14, no. 5: 153.

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