Social Network Analysis (??)Â
Course information
In recent years, Social network analysis has evolved as an interdisciplinary field, drawing from established disciplines such as computer science, physics, social sciences, industrial engineering, and information theory. This field focuses on examining the attributes of connections between entities rather than the characteristics of the entities themselves. For instance, the well-known social science concept of "Six Degrees of Separation" is attributable to specific structural attributes of social networks. Another example is the rapid expansion and success of technologies like the Internet and the Web, which can be attributed to basic dynamic characteristics, such as preferential attachment, found within their network structures.
Tentative Outlines for the courses
Introduction to Large Scale Networks
Measures and Metrics e.g., Centrality measures on degree, eigenvector, Katz, page-rank, betweenness, closeness,..etc
The Large-scale Structure of Networks, e.g., components, funning effect, degree distributions, power law and scale-free networks, clustering coefficeint, assorting mixing
Basic Concepts of Algorithms, e.g., useful data structures, time and space complexity
Fundamental Network Algorithms, e.g., algorithms to determine degree distributions, clustering coefficients, BFS, variants of shortest path, max-flow min-cut
Matrix Algorithms and Graph Partitioning, e.g., dominant eigenvector, graph partitioning, community detection, modularity maximization
Random Graphs, e.g., degree and edges distributions, clustering coefficient, giant and small components, path length
Random Graphs with General Degree Distributions
Networks Formation, e.g, network formation algorithms
Percolation and Network Resilience, e.g., nodes vs. bonds percoloation, network robustness
Epidemics on Networks, e.g., influence models, network stability and information spreading
Dynamic Systems on Networks
Network Search
Network Advertisement
Network Search and Exploration
Game-theoretic Analysis of Online Social Networks
Recitation class
Linear algebra and Probability
Data structure and Algorithm
NetworkX in Python
Related textbook & lecture
Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Online lecture
Complex Network Analysis in Python: Recognize - Construct - Visualize - Analyze - Interpret
Algorithmic techniques for modeling and mining large graphs (AMAzING)