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