Complex Network: Theory and Application

Complex Network: Theory and Application. Instructor: Prof. Animesh Mukherjee, Department of Computer Science and Engineering, IIT Kharagpur. This course covers lessons in network analysis, properties of social networks, community analysis, and case study of citation networks. Study of the models and behaviors of networked systems. Empirical studies of social, biological, technological and information networks. Exploring the concepts of small world effect, degree distribution, clustering, network correlations, node centrality, and community structure of networks. This will be followed by detailed case study of citation networks. Types of network: Social networks, Information networks, Technological networks, Biological networks, Citation Networks. Properties of network: Small world effect, transitivity and clustering, degree distribution, scale free networks, maximum degree; mixing patterns; degree correlations; community structures; node centrality. (from

Lecture 07 - Network Analysis VI: Co-citation Index, Rich-Club Coefficient, ...

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Lecture 01 - Introduction
Lecture 02 - Network Analysis I: Degree of Distribution: The Case of Citation Networks
Lecture 03 - Network Analysis II: Clustering Coefficient, Centrality
Lecture 04 - Network Analysis III: Centrality (Betweenness, Flow Betweenness, Eigenvector)
Lecture 05 - Network Analysis IV: Eigenvector Centrality, PageRank
Lecture 06 - Network Analysis V: PageRank, Hubs and Authorities
Lecture 07 - Network Analysis VI: Co-citation Index, Rich-Club Coefficient, Entropy of the Degree Distribution
Lecture 08 - Social Network Principles I: Assortativity/Homophily, Signed Graphs
Lecture 09 - Social Network Principles II: Social Cohesiveness, Social Roles
Lecture 10 - Social Network Principles III: Social Roles - Equivalences
Lecture 11 - Social Network Principles IV: Social Roles - Equivalences (cont.)
Lecture 12 - Community Analysis I
Lecture 13 - Community Analysis II: Bisective Approach
Lecture 14 - Community Analysis III: Bisection Method - Edge Betweenness
Lecture 15 - Community Analysis IV: Modularity Optimization
Lecture 16 - Community Analysis V: Spectral Bisection
Lecture 17 - Community Analysis VI: Spectral Bisection (cont.)
Lecture 18 - Citation Analysis I: Citation Networks
Lecture 19 - Citation Analysis II: Citation Diversity Index
Lecture 20 - Citation Analysis III: Citation Profiles, Citation Prediction
Lecture 21 - Citation Analysis IV