Dynamic social graphs: mining and modeling

Bijan Ranjbar-Sahraei

Research output: ThesisDoctoral ThesisInternal

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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: Maastricht University.
Ranjbar-Sahraei, Bijan. / Dynamic social graphs : mining and modeling. Maastricht : Maastricht University, 2016.
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keywords = "social graphs, social data, identity resolution, relation extraction, dynamical systems, hierarchical structures, evolution of cooperation",
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year = "2016",
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publisher = "Maastricht University",
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Ranjbar-Sahraei, B 2016, 'Dynamic social graphs: mining and modeling', Maastricht University, Maastricht.

Dynamic social graphs : mining and modeling. / Ranjbar-Sahraei, Bijan.

Maastricht : Maastricht University, 2016.

Research output: ThesisDoctoral ThesisInternal

TY - THES

T1 - Dynamic social graphs

T2 - mining and modeling

AU - Ranjbar-Sahraei, Bijan

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - social graphs

KW - social data

KW - identity resolution

KW - relation extraction

KW - dynamical systems

KW - hierarchical structures

KW - evolution of cooperation

M3 - Doctoral Thesis

SN - 9789462334021

PB - Maastricht University

CY - Maastricht

ER -

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