R language uses clustering algorithm for social network analysis

Table of contents

foreword

data preparation

Build a clustering model

Result analysis

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Today, we are going to discuss how to use clustering algorithms for social network analysis. Clustering is an unsupervised learning method that helps us discover structure and patterns in data. In social network analysis, we can use clustering algorithms to discover communities in the network, that is, areas with dense connections between nodes. In this article, we will use R language and its powerful network analysis library igraph to conduct social network analysis.

foreword

In social networks, an important task is to find communities in the network. This is because, in many cases, communities often correspond to some meaningful groups in the real world, such as circles of friends, interest groups, etc. In order to find the communities in the network, we need a method that can divide the network