Community detection in networks: Structural communities versus ground truth

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Community detection in networks: Structural communities versus ground truth. / Hric, Darko; Darst, Richard K.; Fortunato, Santo.

In: Physical Review E, Vol. 90, No. 6, 062805, 2014, p. 1-19.

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@article{836f5b0474854e8f9154cc7f0c600cc8,
title = "Community detection in networks: Structural communities versus ground truth",
abstract = "Algorithms to find communities in networks rely just on structural information and search for cohesive subsets of nodes. On the other hand, most scholars implicitly or explicitly assume that structural communities represent groups of nodes with similar (nontopological) properties or functions. This hypothesis could not be verified, so far, because of the lack of network datasets with information on the classification of the nodes. We show that traditional community detection methods fail to find the metadata groups in many large networks. Our results show that there is a marked separation between structural communities and metadata groups, in line with recent findings. That means that either our current modeling of community structure has to be substantially modified, or that metadata groups may not be recoverable from topology alone.",
author = "Darko Hric and Darst, {Richard K.} and Santo Fortunato",
year = "2014",
doi = "10.1103/PhysRevE.90.062805",
language = "English",
volume = "90",
pages = "1--19",
journal = "Physical Review E",
issn = "2470-0045",
publisher = "American Physical Society",
number = "6",

}

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TY - JOUR

T1 - Community detection in networks: Structural communities versus ground truth

AU - Hric, Darko

AU - Darst, Richard K.

AU - Fortunato, Santo

PY - 2014

Y1 - 2014

N2 - Algorithms to find communities in networks rely just on structural information and search for cohesive subsets of nodes. On the other hand, most scholars implicitly or explicitly assume that structural communities represent groups of nodes with similar (nontopological) properties or functions. This hypothesis could not be verified, so far, because of the lack of network datasets with information on the classification of the nodes. We show that traditional community detection methods fail to find the metadata groups in many large networks. Our results show that there is a marked separation between structural communities and metadata groups, in line with recent findings. That means that either our current modeling of community structure has to be substantially modified, or that metadata groups may not be recoverable from topology alone.

AB - Algorithms to find communities in networks rely just on structural information and search for cohesive subsets of nodes. On the other hand, most scholars implicitly or explicitly assume that structural communities represent groups of nodes with similar (nontopological) properties or functions. This hypothesis could not be verified, so far, because of the lack of network datasets with information on the classification of the nodes. We show that traditional community detection methods fail to find the metadata groups in many large networks. Our results show that there is a marked separation between structural communities and metadata groups, in line with recent findings. That means that either our current modeling of community structure has to be substantially modified, or that metadata groups may not be recoverable from topology alone.

UR - http://journals.aps.org/pre/abstract/10.1103/PhysRevE.90.062805

U2 - 10.1103/PhysRevE.90.062805

DO - 10.1103/PhysRevE.90.062805

M3 - Article

VL - 90

SP - 1

EP - 19

JO - Physical Review E

JF - Physical Review E

SN - 2470-0045

IS - 6

M1 - 062805

ER -

ID: 805934