Degree Centrality

Introduction

Degree centrality is a concept in network analysis that measures the importance or prominence of a node within a graph. In simple terms, it quantifies the number of direct connections a node has with other nodes in the network. A higher degree centrality indicates that a node has more connections, making it more influential or central within the graph.

Degree centrality can be applied to social network analysis. Imagine we are analyzing a social media platform like Twitter, and we want to find out which users are the most influential based on their connections (i.e., followers and followees). In this context, degree centrality can be used to measure the importance of each user in the network. Users with a high degree centrality would have many followers and followees, indicating that they are well-connected and potentially more influential in the network.

Degree centrality can also help identify key players in various other domains, such as communication networks, transportation systems, or scientific collaboration networks. By understanding which nodes are more central or influential, stakeholders can make informed decisions, allocate resources more efficiently, or devise targeted interventions.

Example of degree centrality

Let's consider a simple social network where people are represented as nodes, and friendships between them are represented as edges.