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Author Peixoto, Tiago, author.

Title Descriptive vs. inferential community detection in networks : pitfalls, myths, and half-truths / Tiago P. Peixoto.

Publication Info. Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2023.
©2023

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Location Call No. Status
 University of Saint Joseph: Pope Pius XII Library - Internet  WORLD WIDE WEB E-BOOK CAMBRIDGE    Downloadable
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Description 1 online resource.
Series Cambridge elements. Elements in structure and dynamics of complex networks
Cambridge elements. Elements in the structure and dynamics of complex networks.
Note Description based on online resource; title from digital title page (viewed on July 11, 2023).
Summary Community detection is one of the most important methodological fields of network science, and one which has attracted a significant amount of attention over the past decades. This area deals with the automated division of a network into fundamental building blocks, with the objective of providing a summary of its large-scale structure. Despite its importance and widespread adoption, there is a noticeable gap between what is arguably the state-of-the-art and the methods which are actually used in practice in a variety of fields. The Elements attempts to address this discrepancy by dividing existing methods according to whether they have a 'descriptive' or an 'inferential' goal. While descriptive methods find patterns in networks based on context-dependent notions of community structure, inferential methods articulate a precise generative model, and attempt to fit it to data. In this way, they are able to provide insights into formation mechanisms and separate structure from noise. This title is also available as open access on Cambridge Core.
Local Note Cambridge University Press Cambridge Open Access Books and Elements
Subject Social networks -- Research -- Methodology.
Social networks -- Research -- Methodology. (OCoLC)fst01122689
ISBN 9781009118897 electronic book
1009118897 electronic book
9781009113007
1009113003
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