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Description
  • The analysis of social networks is concentrated especially on uncovering hidden relations and properties of network members (vertices). Most of the current approaches are focused mainly on different network types and different network coefficients. On one hand, the analysis can be relatively simple; on the other hand some complex approaches to network dynamics can be used. This paper introduces a novel aspect of network analysis based on the so-called Forgetting Curve. For network vertices and edges, we define two coefficients, which describe their role in the network depending on their long-term behavior. Using one of these parameters we reduce the network to smaller components. We provide some experimental results using DBLP dataset. Our research illustrates the usefulness of the proposed approach.
  • The analysis of social networks is concentrated especially on uncovering hidden relations and properties of network members (vertices). Most of the current approaches are focused mainly on different network types and different network coefficients. On one hand, the analysis can be relatively simple; on the other hand some complex approaches to network dynamics can be used. This paper introduces a novel aspect of network analysis based on the so-called Forgetting Curve. For network vertices and edges, we define two coefficients, which describe their role in the network depending on their long-term behavior. Using one of these parameters we reduce the network to smaller components. We provide some experimental results using DBLP dataset. Our research illustrates the usefulness of the proposed approach. (en)
Title
  • Social network reduction based on stability
  • Social network reduction based on stability (en)
skos:prefLabel
  • Social network reduction based on stability
  • Social network reduction based on stability (en)
skos:notation
  • RIV/61989100:27240/10:86085130!RIV13-GA0-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/09/1494)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 288120
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/10:86085130
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Visualization; Stability; Social network reduction; Memory; Complexity reduction; Co-authorship network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [19C691EE458A]
http://linked.open...v/mistoKonaniAkce
  • Taiyuan
http://linked.open...i/riv/mistoVydani
  • Los Alamitos
http://linked.open...i/riv/nazevZdroje
  • 2010 International Conference on Computational Aspects of Social Networks
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Abraham Padath, Ajith
  • Horák, Zdeněk
  • Snášel, Václav
  • Kudělka, Miloš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/CASoN.2010.120
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 978-0-7695-4202-7
http://localhost/t...ganizacniJednotka
  • 27240
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