06.03.2020 Mid-Term project presentation on March 14.

11.02.2020 Extra class on Feb 13 (Thu) from 19.00-20.00. Venue: CS-119

28.01.2020 Extra class on Jan 30 (Thu) from 19.00-20.00. Venue: CS-119

21.01.2020 Extra class on Jan 23 (Thu) from 19.00-20.00. Venue: CS-119

21.01.2020 Term project option submission deadline : Jan. 25 EOD (Hard deadline)

13.01.2020 Term project group submission deadline : Jan. 19 EOD (Hard deadline)

05.01.2020 First class: Jan 13, 2020, Monday. Venue: CS 119, Time: 11.00.

Course outline

General Information

Lectures

Evaluation

Assignments

Overview of Network science, Motivation, Large scale dynamic networks, Challenges of graph theory

Small world effect, transitivity and clustering, degree distribution, scale free networks, maximum degree; network resilience; mixing patterns; degree correlations; community structures; network navigation

Basic concepts of network communities, Modularity, various community finding approaches like Girvan-Newman Algorithm, Spectral Bisection Algorithm, Radicchi Edge Clustering Algorithm (for binary as well as weighted graphs), Wu-Hubermann Algorithm, and Random Walk based Algorithm, Louvain, InfoMap

Poisson random graphs, generalized random graphs, the configuration model, generating functions, power-law degree distribution, directed graph, bipartite graph, degree correlations

Price model, Barabasi & Albert model, other growth models, vertex copying models, Bipartite Network

Percolation theory and network resilience, Epidemiological processes, Cascades and information spread

Homophily, Cohesiveness, Cliques, Clans, Clubs, Plex, Equivalence of ties, Ego-centric networks, Cascade formation and information diffusion in Social media (say Twitter).

Search on networks, exhaustive network search, guided network search, network navigation; network visualization and semantic zooming.

Temporal network, Multilayer networks, Interdependent networks, Controllability of complex networks, Economic and financial network analytics

1. Networks: An Introduction, Oxford University Press, Oxford, 2010.

2. Evolution of Networks, Oxford University Press, Oxford, 2003.

3. The structure and function of complex networks, SIAM Review 45, 167-256, 2003.

4. Statistical mechanics of complex networks, Rev. Mod. Phys., 74(1), 2002.

5. Papers from the ACM and IEEE digital libraries.

Room # : CSE-119

Units : 3-0-0

Credits : 3

Contact : Room #322 (CSE), Phone 82358

Class attendance is mandatory! Any time your attendance falls below 85%, you have 100% chance of being de-registered irrespective of your class performance, CGPA etc!

Mid-sem : 30

End-sem : 40

Graph Theory Basics (Resource 1, Resource 2)

General Reference: Introduction to Network Science

1. Introduction (Paper).

2. Network Analysis (Paper1, Paper2, Paper3).

3. Equivalence & Social Cohesivity (Paper1, Paper2, Paper3, Paper4)

4. Community Detection (General reference, Paper1, Paper2, BFS1, BFS2, K-L, Louvain, Assortative mixing).

5. Random graph (Paper1, Paper2)

6. Growth Models (Paper1)