Research output

Dynamic social graphs: mining and modeling

Research output: ThesisDoctoral ThesisInternal

Standard

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

Maastricht : Maastricht University, 2016.

Research output: ThesisDoctoral ThesisInternal

Harvard

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

APA

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

Vancouver

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

Author

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

Bibtex

@phdthesis{8ee46fa83e8d457d991f49413eb34258,
title = "Dynamic social graphs: mining and modeling",
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.",
keywords = "social graphs, social data, identity resolution, relation extraction, dynamical systems, hierarchical structures, evolution of cooperation",
author = "Bijan Ranjbar-Sahraei",
year = "2016",
language = "English",
isbn = "9789462334021",
publisher = "Maastricht University",
school = "Maastricht University",

}

RIS

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 -