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19-475-0303: COMPLEX NETWORKS: THEORY AND APPLICATIONS
Core/Elective: Elective Semester: 3 Credits: 4
Course Description

Complex networks provide a powerful abstraction of the structure and dynamics of diverse kinds of interaction viz people or people-to-technology, as it is encountered in today’s inter-linked world. This course provides the necessary theory for understanding complex networks and applications built on such backgrounds

Course Objectives

Representation and analysis of complex networks

Course Content

Module I
Networks of information – Mathematics of networks – Measures and metrics – Large scale structure of networks – Matrix algorithms and graph partitioning

Module II
Network models – Random graphs – walks on graphs - Community discovery – Models of network formation – Small world model - Evolution in social networks – Assortative mixingReal networks - Evolution of random network - Watts-Strogatz model – Clustering coefficient - Power Laws and Scale-Free Networks – Hubs - Barabasi-Albert model – measuring preferential attachment- Degree dynamics – non-linear preferential attachment

Module III
Processes on networks – Percolation and network resilience – Epidemics on networks – Epidemic modelling - Cascading failures – building robustness- Dynamical systems on networks – The Bianconi-Barabási model – fitness measurement – Bose-Einstein condensation

Module IV
Models for social influence analysis – Systems for expert location – Link prediction – privacy analysis – visualization – Data and text mining in social networks - Social tagging Module V Social media - Analytics and predictive models – Information flow – Modelling and prediction of flow -Missing data - Social media datasets – patterns of information attention – linear influence model – Rich interactions

REFERNCES

1. Mark J. Newman, Networks: An introduction, 1e, Oxford University Press, 2010
2. Charu C Aggarwal (ed.), Social Network Data Analytics, 1e, Springer, 2011
3. David Easley and Jon Kleinberg, Networks, Crowds, and Markets: Reasoning about a highly connected World, 1e, Cambridge University Press, 2010
4. Albert-Laszlo Barabasi, Network Science, 1e, Cambridge University Press, 2016


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