Title
Испитивање својстава комплексних мрежа са дискретном динамиком
Creator
Smiljanić, Jelena M., 1987-
Copyright date
2017
Object Links
Select license
Autorstvo-Nekomercijalno 3.0 Srbija (CC BY-NC 3.0)
License description
Dozvoljavate umnožavanje, distribuciju i javno saopštavanje dela, i prerade, ako se navede ime autora na način odredjen od strane autora ili davaoca licence. Ova licenca ne dozvoljava komercijalnu upotrebu dela. Osnovni opis Licence: http://creativecommons.org/licenses/by-nc/3.0/rs/deed.sr_LATN Sadržaj ugovora u celini: http://creativecommons.org/licenses/by-nc/3.0/rs/legalcode.sr-Latn
Language
Serbian
Cobiss-ID
Theses Type
Doktorska disertacija
description
Datum odbrane: 16. 11. 2017.
Other responsibilities
mentor
Radovanović, Jelena, 1973-
član komisije
Milanović, Vitomir, 1947-
član komisije
Mitrović-Dankulov, Marija.
član komisije
Rašajski, Marija, 1971-
član komisije
Balaž, Antun, 1973-
Academic Expertise
Prirodno-matematičke nauke
Academic Title
-
University
Univerzitet u Beogradu
Faculty
Elektrotehnički fakultet
Alternative title
Analysis of properties of complex networks with discrete dynamics
Publisher
[Ј. М. Смиљанић]
Format
99 листова
description
Електротехника и рачунарство-Наноелектроника и фотоника / Electrical and computer engineering/nanoelectronics and photonics
Abstract (sr)
Комплексне мреже су се у току последње две деценије показале као изузетно користан концепт у проучавању карактеристика комплексних система...
Abstract (en)
In the last two decades, complex networks have been proven as very useful
concept for examination of properties of complex systems. The first step within
this framework is to extract individual elements of the system and to represent
interactions between these elements in the form of complex network. After this step,
the study of complex system organization is reduced to the analysis of structure and
dynamical processes on network with the use of suitable methodology.
The increase in a variety of real systems with available data, which enable insight
into the structure of network of interactions, requires constant development of new
techniques and theoretical models that could explain behavior of specific systems.
In this thesis, we studied complex networks with discrete dynamics using data on
event-based social systems. There has been very little previous research on properties
of networks representing these systems. One of the main reasons is availability of
data. In the given systems individuals interact face-to-face, wherefore it is more
difficult to get the data, than in the case of social systems where individuals use
some communication device to communicate with each other.
Special attention was paid to examination of activity of individuals in group
events. According to the results of statistical analysis of empirical data it has been
shown that individuals do not attend events randomly. We analysed mathematical
models that can explain member’s participation patterns on events which turned
out to be strongly heterogeneous. It has been shown that generalized binary P´olya
model can reproduce given empirical results successfully.
Using bipartite networks ensemble with maximum entropy, we identified significant
connections in weighted network that represent relevant social interactions. In order
to get the insight into evolution of the network structure, we analyzed change of
local structural parameters after each event attendance. It has been shown that
members of the system establish new connections with neighbors during member’s
early involvement in the group activities, while later, as number of attended events
increase, the interactions with neighbors and strenghtening of existing communities
become preferred in comparison to forming new connections in network.
In order to analyse the influence that particular event has on network structure,
we proposed an approach based on event removal according to different criteria and
examination of resulting structural changes in network. The results showed that
interactions between individuals with strong connections are dominant on events
with small number of members, with small number of members, while during the large events typically individuals
with weak connections that could be easily broken interact.
Authors Key words
комплексне мреже, социофизика, еволуција структуре мреже у времену, моделирање динамичких процеса на мрежи
Authors Key words
complex networks, sociophysics, evolution of network structure in time,
modeling of dynamical processes on network
Classification
004.738.5:316.472(043.3)
Type
Tekst
Abstract (sr)
Комплексне мреже су се у току последње две деценије показале као изузетно користан концепт у проучавању карактеристика комплексних система...
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