Table of Contents
Graph theory provides a mathematical framework for analyzing social networks. It helps identify relationships, influential nodes, and network structures. This article explores practical examples and calculations used in social network analysis.
Basic Concepts in Graph Theory
A social network can be represented as a graph, where individuals are nodes and relationships are edges. Key concepts include degree, path, and connectivity.
Practical Examples
In social network analysis, graph theory helps identify influential individuals, clusters, and information flow. For example, calculating the degree of nodes reveals who has the most connections.
Common Calculations
Some common calculations include:
- Degree Centrality: Counts the number of direct connections a node has.
- Clustering Coefficient: Measures the likelihood that two neighbors of a node are connected.
- Shortest Path: Finds the minimum number of steps between two nodes.
- Betweenness Centrality: Indicates nodes that act as bridges within the network.