Centrality measures on networks and empirical analysis on activity driven network models

Duman, Ece Naz (2015) Centrality measures on networks and empirical analysis on activity driven network models. [Thesis]

[thumbnail of EceNazDuman_10086546.pdf] PDF

Download (2MB)


Social network analysis involves structural studies on social networks, and it benefits measures of graph theory. Centrality indicators are one of these measures, and they map the characteristics of networks. In the first part of this thesis we study the effects of centrality measures on various network types, including degree, closeness and betweenness centrality. Connections in social networks are rapidly changing, through triadic closures, membership closures or foci closures. Correspondingly, the second part of this thesis and the main objective is first to imitate modeling of an evolving network which thoroughly repeats the behavior of real life networks, and then study triadic closures and topological features of this model. Generation of this model includes power law distribution; thus, its degree distribution and other properties resemble features of three studied datasets. Our analysis on this model gives novel results since the model forms triadic closures as in actual social networks. At the end of our analysis we discuss the reasons of triadic closures in this model with the help of centrality indicators and clustering coefficient.
Item Type: Thesis
Additional Information: Yükseköğretim Kurulu Tez Merkezi Tez No: 418617.
Uncontrolled Keywords: Power Laws. -- Evolving Network. -- Triadic Closures. -- Centrality Indicators. -- Kuvvet Yasası. --Gelişen Ağlar. -- Üçlü Kapanımlar. -- Merkeziyet Ölüleri.
Subjects: T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: IC-Cataloging
Date Deposited: 07 May 2018 14:38
Last Modified: 26 Apr 2022 10:21
URI: https://research.sabanciuniv.edu/id/eprint/34694

Actions (login required)

View Item
View Item