Research output

Dynamic social graphs: mining and modeling

Research output: ThesisDoctoral ThesisInternal

Associated researcher

Associated organisations

Abstract

In recent decades, we have faced an explosion of social data, in which unprecedented variety of personal information has become accessible to the public. Social data consists of data on individuals and on interactions among individuals. Once we integrate these two categories of social data, social graphs emerge.
In this research, two main research challenges were addressed: how to turn social data into social graphs and how to analyze the evolving social graphs. In this thesis, effective data-driven approaches were proposed for turning heterogeneous social data into social graphs that successfully revealed new demographic patterns in real historical data corpora.

    Research areas

  • social graphs, social data, identity resolution, relation extraction, dynamical systems, hierarchical structures, evolution of cooperation

Documents

  • Full text

    Final published version, 14 MB, PDF-document

  • Abstract

    Final published version, 99 KB, PDF-document

  • Propositions

    Final published version, 34 KB, PDF-document

  • Cover

    Final published version, 1 MB, image/jpeg

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Details

Original languageEnglish
Awarding Institution
Supervisors/Advisors
Award date28 Oct 2016
Place of PublicationMaastricht
Publisher
  • Maastricht University
Print ISBNs9789462334021
Electronic ISBNs9789462334021
Publication statusPublished - 2016