<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/CINECAstyle.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-23T11:50:43Z</responseDate><request verb="GetRecord" identifier="oai:iris.unica.it:11584/266244" metadataPrefix="oai_dc">https://iris.unica.it/oai/request</request><GetRecord><record><header><identifier>oai:iris.unica.it:11584/266244</identifier><datestamp>2022-10-20T09:01:38Z</datestamp><setSpec>com_11584_207615</setSpec><setSpec>com_11584_111066</setSpec><setSpec>col_11584_265854</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>Models and frameworks for studying social behaviors</dc:title>
<dc:creator>JAVARONE, MARCO ALBERTO</dc:creator>
<dc:subject>Reti complesse</dc:subject>
<dc:subject>complex networks</dc:subject>
<dc:subject>complex systems</dc:subject>
<dc:subject>comportamenti sociali</dc:subject>
<dc:subject>dinamica sociale</dc:subject>
<dc:subject>sistemi complessi</dc:subject>
<dc:subject>social behaviors</dc:subject>
<dc:subject>social dynamics</dc:subject>
<dc:subject>Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni</dc:subject>
<dc:description>Studies on social systems and human behavior are typically considered domain of humanities and psychology. However, it appears that recently these issues have attracted a strong interest also from the scienti�c community belonging to the hard sciences {in particular from physics, computer science&#xd;
and mathematics. The network theory o�ers powerful tools to study social systems and human behavior. In particular, complex networks have gained a lot of prestige as general framework for representing and analyze real systems.&#xd;
From an historical perspective, complex networks are rooted in graph theory {which in turn is dated back to 1736, when Leonhard Euler wrote the paper on the seven bridges of K�onigsberg. After Euler's work, di�erent mathematicians (e.g. Cayley) focused their research on graphs {opening the&#xd;
possibility of applying their results to deal with theoretical and real problems. As a result, complex networks emerged as multidisciplinary approach&#xd;
for studying complex systems. From a computational perspective, models based on complex networks allows to extract information on complex systems composed by a great number of interacting elements. A variety of systems&#xd;
can be modelled as a complex network (e.g. social networks, the World Wide Web, internet, biological systems, and ecological systems). To summarize, any such system should give the possibility of viewing its elements as&#xd;
simple (at some degree of abstraction), while assuming the existence of nonlinear interactions, the absence of a central control, and emergent behavior. Nowadays, scientists belonging to di�erent communities use complex networks as a framework for dealing with their preferred research issues, from a theoretical and/or pratical perspective. This work is aimed at illustrating&#xd;
some models, based on complex networks, deemed useful to represent social behaviors like competitive dynamics, groups formation, and emergence of linguistics phenomena.</dc:description>
<dc:date>2013-04-23</dc:date>
<dc:type>info:eu-repo/semantics/doctoralThesis</dc:type>
<dc:identifier>http://hdl.handle.net/11584/266244</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>numberofpages:78</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:publisher>Università degli Studi di Cagliari</dc:publisher>
<dc:rights>license:Non specificato</dc:rights>
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