Search results for "Social network analysi"

showing 10 items of 89 documents

A Comparison of Dyadic and Social Network Assessments of Peer Influence.

2021

The present study compares two methods for assessing peer influence: the longitudinal actor–partner interdependence model (L-APIM) and the longitudinal social network analysis (L-SNA) Model. The data were drawn from 1,995 (49% girls and 51% boys) third grade students ( Mage= 9.68 years). From this sample, L-APIM ( n = 206 indistinguishable dyads and n = 187 distinguishable dyads) and L-SNA ( n = 1,024 total network members) subsamples were created. Students completed peer nominations and objective assessments of mathematical reasoning in the spring of the third and fourth grades. Patterns of statistical significance differed across analyses. Stable distinguishable and indistinguishable L-AP…

Social Psychologysocial network analysisLogical reasoningmedia_common.quotation_subjectkoululaisetsosiaalinen vuorovaikutusArticleEducationDevelopmental Neurosciencesosiaaliset verkostot0502 economics and businesssocial contextDevelopmental and Educational PsychologyPeer influencedyadic data analysismatemaattiset taidotvertaisoppiminen0501 psychology and cognitive sciencesLife-span and Life-course StudiesDyadic data analysismedia_commonpeer influenceSocial networkbusiness.industry4. Educationlongitudinal methods05 social sciencesSocial network analysis (criminology)Social environmentalakoululaisetsosiaaliset suhteetFriendshippeer relationshipsbusinessPsychologySocial psychology050203 business & managementSocial Sciences (miscellaneous)vertaissuhteet050104 developmental & child psychologyNetwork analysisInternational journal of behavioral development
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Multilayer Network Analysis: The Identification of Key Actors in a Sicilian Mafia Operation

2021

Recently, Social Network Analysis studies have led to an improvement and to a generalization of existing tools to networks with multiple subsystems and layers of connectivity. These kind of networks are usually called multilayer networks. Multilayer networks in which each layer shares at least one node with some other layer in the network are called multiplex networks. Being a multiplex network does not require all nodes to exist on every layer. In this paper, we built a criminal multiplex network which concerns an anti-mafia operation called “Montagna” and it is based on the examination of a pre-trial detention order issued on March 14, 2007 by the judge for preliminary investigations of t…

Social and Information Networks (cs.SI)FOS: Computer and information sciencesPhysics - Physics and SocietyFocus (computing)Settore INF/01 - InformaticaMultilayer networksComputer sciencebusiness.industryNode (networking)Criminal networks; Multilayer networks; Social network analysisSocial network analysis (criminology)FOS: Physical sciencesComputer Science - Social and Information NetworksPhysics and Society (physics.soc-ph)Criminal networksSocial network analysisIdentification (information)PhoneKey (cryptography)Layer (object-oriented design)businessNetwork analysisComputer network
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Correlations among Game of Thieves and other centrality measures in complex networks

2021

Social Network Analysis (SNA) is used to study the exchange of resources among individuals, groups, or organizations. The role of individuals or connections in a network is described by a set of centrality metrics which represent one of the most important results of SNA. Degree, closeness, betweenness and clustering coefficient are the most used centrality measures. Their use is, however, severely hampered by their computation cost. This issue can be overcome by an algorithm called Game of Thieves (GoT). Thanks to this new algorithm, we can compute the importance of all elements in a network (i.e. vertices and edges), compared to the total number of vertices. This calculation is done not in…

Social and Information Networks (cs.SI)FOS: Computer and information sciencesTheoretical computer scienceCentrality measureDegree (graph theory)Settore INF/01 - InformaticaComputer scienceClosenessSocial network analysiComputer Science - Social and Information NetworksComplex networkComplex networkBetweenness centralityCorrelation coefficientsCentralityTime complexitySocial network analysisClustering coefficient
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Fragile Correctness of Social Network Analysis

2016

Draft version of the paper

Social network analysis:TECHNOLOGY::Information technology::Computer science [Research Subject Categories]CorrectnessGraph algorithmsGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)
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Análisis relacional en iniciativas socialmente innovadoras. El caso de estudio de Alianza Mar Blava (Ibiza-Formentera)

2019

Los estudios de desarrollo local, durante los últimos años, han recuperado la innovación social cómo perspectiva analítica de los cambios organizativos y procesos de transformación de las relaciones sociales en el territorio. Con ello, surge el interés de cómo estudiar lo intangible de esta dimensión del desarrollo local. A partir de aquí, el capital social cobra especial interés como enfoque teórico para poder interpretar el análisis relacional. Así, mediante el caso de estudio de una iniciativa socialmente innovadora (Alianza Mar Blava, en el área de Ibiza y Formentera), esta investigación identifica la red social de actores relevantes y caracteriza las redes personales y otros atributos …

Social networkbusiness.industryWelfare economicsGeography Planning and DevelopmentControl (management)AttributiveSocial relationPower (social and political)soccer.teamsoccerSociologybusinessFormenteraSocial network analysisEarth-Surface ProcessesSocial capitalCuadernos Geográficos
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Trends in scientific research on climate change in agriculture and forestry subject areas (2005–2014)

2017

The term “Climate change” involves an alteration of the mean and variability of the climate properties. It implies unusual variations in the planet earth atmosphere, which causes related effect on other parts of the planet. The reduction in the land crops annual yield is derived from those alterations. The objective of this paper was to contribute to a better understanding of the scientific knowledge of climate change and its effect concerning agriculture and investigate its evolution through published papers. The items under study were obtained from the Web of Science (WOS) platform from Thomson Reuters. A bibliometric and social network analysis was performed to determine the indicators o…

Sociology of scientific knowledge010504 meteorology & atmospheric sciencesTECNOLOGIA DE ALIMENTOSStrategy and ManagementDeveloping countryClimate change010501 environmental sciencesBibliometrics01 natural sciencesIndustrial and Manufacturing EngineeringEnvironmental protectionSocial network analysesForest ecologyRegional scienceClimate changeSociologyChinaSocial network analysis0105 earth and related environmental sciencesGeneral Environmental ScienceRenewable Energy Sustainability and the Environmentbusiness.industryAgricultureAgricultureBibliometricsbusinessResearch collaborationJournal of Cleaner Production 147: 406-418 (2017)
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Social Networks as an Approach to Systematic review

2019

Whether we are in the process of designing a new empirical study or our interest lies in conducting a review study, a solid literature review is needed to acquire an accurate idea of the current state of affairs with regard to a phenomenon of interest. Even if we can find contributions to the literature by entering keywords in search engines, we need tools that can help us to structure all the contributions encountered in terms of their interrelations and impact. This article presents social network analysis as such a tool. Although social network analysis is commonly thought of as a method in a particular empirical study, where individuals and groups of participants are studied, we can vie…

Structure (mathematical logic)lcsh:R5-920Empirical researchComputer scienceProcess (engineering)Field (Bourdieu)State of affairsContext (language use)lcsh:Medicine (General)CitationSocial network analysisData scienceHealth Professions Education
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An Analysis of the Internal Organization of Facebook Groups

2019

With the rapid development and growth of online social networks (OSNs), researchers have been pushed forward to improve the knowledge of these complex networks by analyzing several aspects, such as the types of social media, the structural properties of the network, or the interaction patterns among users. In particular, a relevant effort has been devoted to the study and identification of cohesive groups of users in OSNs (also referred as communities) because they are the basic building block of each OSN. While several research works on groups in OSNs have mainly focused on identifying the types of groups and the contents created by their members, the analysis of internal organizations of …

Structure (mathematical logic)social networksExploitSettore INF/01 - InformaticaComputer science020206 networking & telecommunications02 engineering and technologyComplex networkData scienceGroup organization; network centrality; social networks; tie strengthHuman-Computer InteractionIdentification (information)tie strengthModeling and Simulation0202 electrical engineering electronic engineering information engineeringGroup organizationnetwork centrality020201 artificial intelligence & image processingSocial mediaUse casesocial networkSocial network analysisSocial Sciences (miscellaneous)Internal organization
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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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