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Formal Concept Analysis of Social Networks

  • Book
  • © 2017

Overview

Editors:
  1. Rokia Missaoui

    1. Department of Computer Science & Engineering, University of Quebec in Outaouais, Quebec, Canada

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  2. Sergei O. Kuznetsov

    1. Faculty of Computer Science, National Research University Higher School of Economics, Moscow, Russia

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  3. Sergei Obiedkov

    1. Faculty of Computer Science, National Research University Higher School of Economics, Moscow, Russia

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  • Includes an overview of key problems and methods in social network analysis and formal concept analysis
  • Features practical examples of social network analysis with formal concept analysis-based techniques applied to real-life data
  • Contains the latest applications of lattices for the analysis of social data

Part of the book series: Lecture Notes in Social Networks (LNSN)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xviii
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  2. Knowledge Communities and Socio-Cognitive Taxonomies

    • Camille Roth
    Pages 1-18

  3. Individuality in Social Networks

    • Daniel Borchmann, Tom Hanika
    Pages 19-40

  4. Descriptive Community Detection

    • Martin Atzmueller
    Pages 41-58

  5. Multimodal Clustering for Community Detection

    • Dmitry I. Ignatov, Alexander Semenov, Daria Komissarova, Dmitry V. Gnatyshak
    Pages 59-96

  6. Acquisition of Terminological Knowledge from Social Networks in Description Logic

    • Francesco Kriegel
    Pages 97-142

  7. Formal Concept Analysis of Attributed Networks

    • Henry Soldano, Guillaume Santini, Dominique Bouthinon
    Pages 143-170

  8. A Formal Concept Analysis Look at the Analysis of Affiliation Networks

    • Francisco J. Valverde-Albacete, Carmen Peláez-Moreno
    Pages 171-195
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Keywords

About this book

The book studies the existing and potential connections between Social Network Analysis (SNA) and Formal Concept Analysis (FCA) by showing how standard SNA techniques, usually based on graph theory, can be supplemented by FCA methods, which rely on lattice theory.

The book presents contributions to the following areas: acquisition of terminological knowledge from social networks, knowledge communities, individuality computation, other types of FCA-based analysis of bipartite graphs (two-mode networks), multimodal clustering, community detection and description in one-mode and multi-mode networks, adaptation of the dual-projection approach to weighted bipartite graphs, extensions to the Kleinberg's HITS algorithm as well as attributed graph analysis.

Editors and Affiliations

  • Department of Computer Science & Engineering, University of Quebec in Outaouais, Quebec, Canada

    Rokia Missaoui

  • Faculty of Computer Science, National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov, Sergei Obiedkov

About the editors

Rokia Missaoui, is a Professor at the Department of Computer Science and Engineering and the Head of LARIM, the Research Laboratory on Multimedia) at the University of Quebec in Outaouais.

Sergei Obiedkov is an Associate Professor at the Faculty of Computer Science, National Research University of Higher School of Economics, Moscow, Russia.


Sergei Kuznetsov is a Professor at the Faculty of Computer Science, National Research University of Higher School of Economics, Moscow, Russia.

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