Испитивање својстава комплексних мрежа са дискретном динамиком
Analysis of properties of complex networks with discrete dynamics
Author
Smiljanić, Jelena M.Mentor
Radovanović, Jelena
Committee members
Milanović, VitomirMitrović-Dankulov, Marija
Rašajski, Marija

Balaž, Antun

Metadata
Show full item recordAbstract
Комплексне мреже су се у току последње две деценије показале као изузетно користан концепт у проучавању карактеристика комплексних система...
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 system...s 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.