Dynamic social graphs: mining and modeling

Bijan Ranjbar-Sahraei

Research output: ThesisDoctoral ThesisInternal

603 Downloads (Pure)

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.
Original languageEnglish
Awarding Institution
  • Maastricht University
Supervisors/Advisors
  • Weiss, Gerhard, Supervisor
  • Tuyls, Karl, Advisor
Award date28 Oct 2016
Place of PublicationMaastricht
Publisher
Print ISBNs9789462334021
Electronic ISBNs9789462334021
Publication statusPublished - 2016

Keywords

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

Cite this

Ranjbar-Sahraei, B. (2016). Dynamic social graphs: mining and modeling. Maastricht University.