SNA: Lecture 1 - Graph Theory

Social Network Analysis - Graph theory by Vanshika Gupta.
Handwritten Notes - [https://drive.google.com/file/d/13woV...]

Topics: [01:54]
Introduction [07:04]
Types of Graph [10:00]
Adjacency Matrix [16:36]
Incidence Matrix [22:40]
Lamport Matrix (optional) [28:13]
Directed Graph [32:45]
Components of Graph [40:27]
Sparsity and density [53:25]
(lecture 4-5)


Summary:

1. Introduction to Graph Theory:
Graph can be represented by nodes and edges.
Types of graphs: simple, self-loop, heterogeneous, weighted, bipartite.
Agency matrix and incidence matrix.
Lamport matrix (optional).

2. Components in Graphs:
Components are disjoint graphs within a network.
Strongly connected components require a path from A to B and vice versa.
Weakly connected components do not require a reverse path.

3. Sparsity and Density of Graphs:
Sparse networks have more zeros than ones in the adjacency matrix.
Dense networks have more ones than zeros in the adjacency matrix.
Density can also be determined by the number of edges compared to the square of the number of nodes.

4. Next Steps:
Continuing with Lecture 6 in the next session.
Daily classes to cover the syllabus by September 10th.

Note: Timestamps are approximate and may vary slightly depending on the recording.

#socialnetworkanalysis #graphtheory