How can you analyze social network structure, dynamics, and influence?

1 What is a network?

A network, or a graph, is a collection of nodes and edges. Nodes represent entities, such as individuals, organizations, or products, and edges represent connections, such as friendships, collaborations, or transactions. Networks can be characterized by various properties, such as size, density, degree distribution, clustering, centrality, and modularity. These properties can reveal important features of the network structure, such as how connected, diverse, influential, or cohesive it is.

3 How to model network influence?

Network influence refers to how nodes affect each other's behaviors, opinions, or outcomes through their network connections. For example, you might want to know how a node's position or role in the network influences its power, prestige, or performance. Or you might want to know how a node's actions or messages influence its neighbors or the whole network. To model network influence, you can use methods such as network regression, network diffusion, or network game theory. These methods can help you estimate and explain network effects, simulate and predict network outcomes, and optimize and intervene in network strategies.

4 How to visualize network data?

Visualizing network data can help you explore and communicate network insights. Network visualization involves representing nodes and edges as graphical elements, such as points and lines, and arranging them in a meaningful way. Network visualization can be done manually or with software tools, such as Gephi, Cytoscape, or NetworkX. Network visualization can be enhanced by using techniques such as color, size, shape, layout, or animation to highlight network attributes, properties, or dynamics.

5 How to learn network analysis?

Network analysis is a multidisciplinary and versatile skill that can be applied to various domains and problems. To learn network analysis, you can start by reading some introductory books or articles, such as Social Network Analysis by John Scott or A Brief Introduction to Network Analysis by Lada Adamic. You can also take some online courses or workshops, such as Network Analysis in R by DataCamp or Social Network Analysis by Coursera. You can also practice network analysis by using real or simulated data sets and software tools, such as the ones mentioned above.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?