Frontiers of Network Science CSCI-6250/4250 - Fall 2021

Professor: Boleslaw Szymanski — boleslaw.szymanski@gmail.com

Lectures: Mon & Thu 12:00 - 13:40, Lally02

Office Houres: Mon 15:00 - 16:00, Wed 13:00 - 14:00, remote webex

Textbook: Albert Laszlo Barabasi Network Science, Cambridge University Press, 2016

Description: This course offers the introduction to network science and review of current research in this field. Classes will interchangeably present chapters from the textbook and the related current research. The emphasis will be on mathematical background of network science: graphs and networks; random networks and various types of scale-free networks; network properties such as assortatitivity, mobility, robustness, social networks and communities; and dynamics of processes on networks.

Syllabus

Calendar

This is a web page for the class which contains the basic information about the course, lecture notes, assignments and thier solutions, and comments. This page will also contain the corrections and general news about the course.

Course Content includes: (i) Mathematical background of network science: graphs and networks, (ii) Random networks and their properties, (iii) The scale-free property, small world networks and Barabasi-Alert model, (iv) Evolving networks, (v) Degree Correlation (vi) Network robustness, and (vii) Social networks and communities.

Class 1

Overview and Introduction to Network Science (textbook chapter 1)

Overview Introduction to Network Science (pdf)(textbook chapter 1)

Research seminar: Detection of the source of spread in complex networks

Research seminar: Detection of the source of spread in complex networks (pdf)

Class 2

Research seminar: Detection of the source of spread in complex networks Part II

Research seminar (pdf): Detection of the source of spread in complex networks Part II

Introduction to Network Science Part II (textbook chapter 1)

Introduction to Network Science Part II (pdf)(textbook chapter 1)

Class 3

Graph Theory (textbook chapter 2) and Topics for Grad Presentations

Graph Theory (pdf) (textbook chapter 2) and Topics for Grad Presentations

Detailed Topics for Graduate and Undergraduate Presentations still available, selection due before class 6, 9/16/21

Class 4

Graph Theory II (textbook chapter 2)

Graph Theory II (pdf)(textbook chapter 2)

Class 5

Scale Free Networks (textbook chapter 3)

Scale Free Networks (pdf)(textbook chapter 3)

Class 6

Communities in US Senate, Research

Communities in US Senate, Research (pdf)

Polarization in US Congress, Research

Polarization Communities in US Congress, Research (pdf)

Class 7

Polarization II

Polarization II (pdf)

Scale Free Networks II (textbook chapter 3-4)

Scale Free Networks II (pdf)(textbook chapter 3-4)

Class 8

Network Tools - Gephi

Network Tools - Gephi (pdf)

Class 1880-1881 Network in Gephi format

Class 1880-1881 paper

Twitter Influencers in 2016-2020 Presidential Elections

Class 9

Scale Free Networks II (textbook chapter 4)

Scale Free Networks II (pdf)(textbook chapter 4)

Class10

ER-model generator (pdf)

ER-model generator (in c)

BA-model generator (pdf)

BA-model generator (in c)

Barabasi-Albert Model (textbook chapter 5)

Barabasi-Albert Model (pdf) (textbook chapter 5)

Class11

research plans by graduate students:

Quantifying reputation and success in art

Human symptoms disease network

The spreading of misinformation online

Quantifying the evolution of individual scientific impact

Class12

research plans by graduate students:

Betweenness Centrality in static and dynamic graphs

A Network framework of cultural history

The universal decay of collective memory and attention

Quantifying the future lethality of terror organizations

Universal resilience patterns in complex networks

Class13

research plans by graduate students:

Betweenness Centrality in static and dynamic graphs

Cards as Connectors: Exploring the Historical Use and Trends of Card Selection

Controllability of complex networks

Community Detection

A universal model for mobility and migration patterns

Class14

Barabasi-Albert Model II

Barabasi-Albert Model II (pdf)

SIR Model of Pandemics in NYC, Omar Malik, Physics

Class15

Community Struture Uncertainty

Political Polarization

Class16

Degree Correlations part I (textbook chapter 7)

Degree Correlations part I (pdf)(textbook chapter 7) (pdf)

Bio and Social Networks Analysis, Aamir Mandviwalla

Class17

Homework1 Solutions

Degree Correlations part II (textbook chapter 7)

Degree Correlations part II (pdf)(textbook chapter 7) (pdf)

Class18

Class19

Fitness IN BA networks, Lisa Knuckey

Testing Community Detection, Sahith Bhamidipati.pptx

Epidemic Modeling, Shanthni Ravindrababu

Giant Component, Felix Yu

Universality of noise-induced reslilience restoration, Cheng Ma

Degree Correlations part II (textbook chapter 7)

Class20

Human symptoms-disease network, Vijaj Sadashivaiah

Global Risk Networks II

Class21

The spreading of Misinformatoin online, Nkechinyere Agu

Statistical Analysis of Terrorist Attacks, Burak Varici

Class22

Adaptive Multiscale

Univeral_resilience

Class23

Link Mining, Muhammad Saad Atique

Testing_Communities

Transferable Learning James Flamino

Class24

Human Mobility and Migration Patterns, Sharmishtha Dutta

Contact Networks, Emelia Blannkenship

Class25

Giant Component, Felix Yu

Music Genres and Popularity, Michael Mandulak

Class26

Cultural History, M.Crotty

The Effect of Social Media on Minority Viewpoints, S.Francis, M.Kohodak (pdf)

Class27

Epidemic Modeling, Shanthni Ravindrababu

Accelerating dynamics of collective memory, Xin Ning

Community Algorithms, Christopher Maria

Class28

Controlability of Complex Network, Kelsey Rook

Immunization, Sebastian Ungard

Epidemics on Networks, Hairong Chen

Modularity_and_Greedy Algorithms, Stephen Tremple

Growing complex network of citations of scientific papers: Modeling and measurements, Kunyuan Liu