• ISSN: 2148-2225 (online)

Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

Ground Truth in Network Communities and Metadata-Aware Community Detection: A Case of School Friendship Network


Kenan Kafkas

Nazım Ziya Perdahçı, Ph.D.

Mehmet Nazif Aydın, Ph.D.


Real-world networks are everywhere and can represent biological, technological, and social interactions. They constitute complicated structures in terms of type of things and their relations. Understanding the network requires better examination of the network structure that can be achieved at various scales including macro, meso, and micro. This research is concerned with meso scale for a student best friendship network where sub-structures in which groups of entities (students) take different functions. In this study we address the following research questions: To what extent would NeoSBM as a stochastic process underlie best friendship interaction and in turn ground truth interactions (i.e. reported best friendship)? Do metadata such as gender or class contribute to this understanding? How can one support school managers from a meta-data aware community detection perspective? Our findings suggest that metadata aware community detection can be an effective method in supporting decision-making for class formation and group formation for in and out school activities.

Keywords: Best Friends Network, Community Detection, SBM, neoSBM

Jel Classification: C01

Suggested citation

Kafkas, K., Perdahçı, N. Z. & Aydın, M. N. (). Ground Truth in Network Communities and Metadata-Aware Community Detection: A Case of School Friendship Network. Alphanumeric Journal, 9(1), 49-62. http://dx.doi.org/10.17093/alphanumeric.688660


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Volume 9, Issue 1, 2021


alphanumeric journal

Volume 9, Issue 1, 2021

Pages 49-62

Received: Feb. 14, 2020

Accepted: May 6, 2021

Published: June 30, 2021

Full Text [1.1 MB]

2021 Kafkas, K., Perdahçı, NZ., Aydın, MN.

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

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