Course Name: CS6012 : Social Network Analysis

Description: Introduction: Motivation, different sources of network data, types of networks, tools for visualizing network data, review of graph theory basics. Structural properties of networks: Notions of centrality, cohesiveness of subgroups, roles and positions, structural equivalence, equitable partitions, stochastic block models. Cascading properties of networks: Information/influence diffusion on networks, maximizing influence spread, power law and heavy tail distributions, preferential attachment models, small world phenomenon. Mining Graphs: Community and cluster detection: random walks, spectral methods; link analysis for web mining.

Slot: C

RoomNo: CS36

Instructor: Ravindran B

Period: JAN-MAY 2013

This page was created on: Thursday 19th of September 2013 09:37:19 PM