Search results for "SOCIAL NETWORK"

showing 10 items of 537 documents

Statistically validated networks in bipartite complex systems.

2011

Many complex systems present an intrinsic bipartite nature and are often described and modeled in terms of networks [1-5]. Examples include movies and actors [1, 2, 4], authors and scientific papers [6-9], email accounts and emails [10], plants and animals that pollinate them [11, 12]. Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. When one constructs a projected network with nodes from only one set, the system heterogeneity makes it very difficult to identify preferential links between the elements. Here we introduce an unsupervised method to statistically validate each link of the pr…

Theoretical computer scienceComputer sciencelcsh:MedicineNetwork theorySocial and Behavioral SciencesBioinformaticsQuantitative Biology - Quantitative MethodsSociologyProtein Interaction Mappinglcsh:ScienceQuantitative Methods (q-bio.QM)MultidisciplinarySystems BiologyApplied MathematicsPhysicsStatisticsComplex SystemsGenomicsLink (geometry)Social NetworksSpecialization (logic)Interdisciplinary PhysicsBipartite graphProbability distributionResearch ArticleNetwork analysisPhysics - Physics and SocietyComplex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)Type (model theory)BiologyModels BiologicalNetwork theory Statistical PhysicsStatistical MechanicsSet (abstract data type)Statistical MethodsBiologyStructure (mathematical logic)Statistical Physicslcsh:RComputational BiologyModels TheoreticalComparative GenomicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)FOS: Biological sciencesNetwork theorylcsh:QNull hypothesisMathematicsPLoS ONE
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A Logical Key Hierarchy Based approach to preserve content privacy in Decentralized Online Social Networks

2020

Distributed Online Social Networks (DOSNs) have been proposed to shift the control over user data from a unique entity, the online social network provider, to the users of the DOSN themselves. In this paper we focus on the problem of preserving the privacy of the contents shared to large groups of users. In general, content privacy is enforced by encrypting the content, having only authorized parties being able to decrypt it. When efficiency has to be taken into account, new solutions have to be devised that: i) minimize the re-encryption of the contents published in a group when the composition of the group changes; and, ii) enable a fast distribution of the cryptographic keys to all the m…

Theoretical computer scienceFacebookComputer scienceInformation privacyCyber SecurityGroup communicationJoinsEncryptionEncryptioncomputer.software_genreKey managementSet (abstract data type)Peer-to-peer computingElectrical and Electronic EngineeringFocus (computing)VegetationSocial networkSettore INF/01 - Informaticabusiness.industryGroup (mathematics)Composition (combinatorics)Decentralized Online Social NetworksDecentralized Online Social Networks; Encryption; Facebook; Group communication; Information privacy; Key management; Peer-to-peer computing; Privacy; Vegetation; Electrical and Electronic EngineeringPrivacyContent (measure theory)Decentralized online social networkData miningbusinesscomputerData privacy
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Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

2021

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…

Theoretical computer scienceSettore INF/01 - InformaticaComputational complexity theorySocial networkComputer sciencebusiness.industryNode (networking)Complex networksComplex networkSocial network analysisK-pathBetweenness centralityCentrality measuresCorrelation coefficientsCentralitybusinessSocial network analysisClustering coefficient
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Social network analysis: the use of graph distances to compare artificial and criminal networks

2021

Aim: Italian criminal groups become more and more dangerous spreading their activities into new sectors. A criminal group is made up of networks of hundreds of family gangs which extended their influence across the world, raking in billions from drug trafficking, extortion and money laundering. We focus in particular on the analysis of the social structure of two Sicilian crime families and we used a Social Network Analysis approach to study the social phenomena. Starting from a real criminal network extracted from meetings emerging from the police physical surveillance during 2000s, we here aim to create artificial models that present similar properties. Methods: We use specific tools of s…

Theoretical computer sciencesocial network analysisSpectral distanceSettore INF/01 - InformaticaComputer sciencegraph theorySocial network analysis (criminology)social network analysiGraph theoryspectral distancenetwork modelCriminal networksCriminal networkGraph (abstract data type)Criminal networks social network analysis graph theory spectral distance network modelNetwork model
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Heterogeneous network games: Conflicting preferences

2013

Proceeding at: 2nd Annual UECE Lisbon Meeting: Game Theory and Applications, took place 2010, November, 4-6, in Lisbon (Portugal). The event Web site http://pascal.iseg.utl.pt/~uece/lisbonmeetings2010/ In many economic situations, a player pursues coordination or anti-coordination with her neighbors on a network, but she also has intrinsic preferences among the available options. We here introduce a model which allows to analyze this issue by means of a simple framework in which players endowed with an idiosyncratic identity interact on a social network through strategic complements or substitutes. We classify the possible types of Nash equilibria under complete information, finding two thr…

TheoryofComputation_MISCELLANEOUSComputer Science::Computer Science and Game Theoryjel:Z13Economics and EconometricsMatemáticasjel:D85Heterogeneity Networks Nash Equilibrium StabilitySocial networksjel:D03MicroeconomicsCOMPLEMENTARITIESsymbols.namesakeBayesian gameEconomicsCoordination gameStrategic complementsjel:C72ComputingMilieux_PERSONALCOMPUTINGTheoryofComputation_GENERALNetwork formationNash equilibriumEquilibrium selectionBest responsejel:L14Bayesian equilibriumsymbolsHeterogeneityEpsilon-equilibriumMathematical economicsFinanceIncomplete informationGames and Economic Behavior
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A multilevel statistical toolkit to study animal social networks: the Animal Network Toolkit Software (ANTs) R package

2020

Abstract The possible role played by individual attributes, sociodemographic characteristics and/or ecological pressures in the interaction between animals and the development of social relationships between them is of great interest in animal ecology and evolutionary biology. Social Network Analysis is an ideal tool to study these types of questions. The Animal Network Toolkit Software (ANTs) R package was specifically developed to provide all the different social network analysis techniques currently used in the study of animal social networks. This global package enables users to (1) compute global, polyadic and nodal network measures; (2) perform data randomisation: data stream and netw…

Time FactorsEcologySciences du Vivant [q-bio]/Biologie animalelcsh:RStatistics as Topiclcsh:MedicineArticleSocial NetworkingAnimalslcsh:Qlcsh:ScienceZoologyComputingMilieux_MISCELLANEOUS[CHIM.CHEM]Chemical Sciences/CheminformaticsSoftwareVDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480Scientific Reports
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Analyzing Online Social Support Networks. The Case of Italian Time Banks on Facebook

2019

With the advent of the Internet, social support has changed in nature and size, and new forms of social help have emerged, that reshaped the meaning of this concept. In the last years, social support has been mainly investigated within the theoretical framework of relational sociology, using network analysis techniques (Crossley, 2011; Donati, 2011; Mische, 2011; Tronca, 2013). An interesting expression of social support networks and civic engagement is the phenomenon of time banks that has had a broad diffusion in the mid-1990s, after important changes in postindustrial society. These organizations are now trying to exploit the potential of the Internet and social networking sites as a mea…

Time bankcivic engagementtextual analysisSettore SPS/07 - Sociologia GeneraleSocial Network Analysi
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Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis

2020

With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being discussed from such content. Machine learning and natural language processing algorithms are used to analyze the massive amount of textual social media data available online, including topic modeling techniques that have gained popularity in recent years. This paper investigates the topic modeling subject and its common application areas, methods, and tools. Also, we examine and compare five frequen…

Topic modelshort textInformation retrievalSocial networkbusiness.industryLatent semantic analysisComputer scienceRandom projectiontopic modelingUser-generated contentSubject (documents)Context (language use)Latent Dirichlet allocationlcsh:QA75.5-76.95symbols.namesakeArtificial Intelligenceonline social networkssymbolsMethodslcsh:Electronic computers. Computer sciencenatural language processingbusinessuser-generated contentFrontiers in Artificial Intelligence
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A Relational Approach to Networks in a Tourism Destination: Business and Family Networks in San Vito Lo Capo, Sicily

2022

This article constructs a relational framework using the principles of the Network Approach to examining the business exchange structure of a tourist destination. Network Analysis is the methodology to analyse the metrics of collaboration and cooperation among destination companies. The model was applied in a remote tourist destination named San Vito Lo Capo on the island of Sicily, where tourism has significantly expanded in the last twenty years. The focus is on how groupings of small companies within family relations can govern and be responsible for tourism destination cooperation. As the main result, the existence was identified, of a relational framework where three clusters of famili…

Tourism and Travelsocial network analysis tourism destination tourism businesstourism destinationsocial network analysisGeographyEconomicstourism businessSettore SECS-P/06 - Economia ApplicataTourism
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Tourist destination network analysis: The ego network role

2017

This paper aims to analyse the different roles that enterprises have within a tourist destination by identifying the presence and possible role of leaders within the system. The Social Network Analysis (SNA) is a tool that offers a greater degree of understanding of the operation of the destination. The map of commercial relations between the leading players of tourist supply can provide greater insight into the main relations existing between enterprises and the principles that ensure and regulate operation. In keeping with this objective and building on the results of a previous paper (Iannolino and Ruggieri, 2012), the authors have focused their attention on the role of some enterprises …

Tourism Leisure and Hospitality ManagementGeography Planning and DevelopmentSettore SECS-P/06 - Economia Applicatatourism destination social network analysis ego-network family cluster sub-network influence
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