Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks.
This book provides a quick start guide to network analysis and visualization in R.
You'll learn, how to:
- Create static and interactive network graphs using modern R packages.
- Change the layout of network graphs.
- Detect important or central entities in a network graph.
- Detect community (or cluster) in a network.
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This section contains best data science and self-development resources to help you on your path.
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- Specialization: Statistics with R by Duke University
- Specialization: Software Development in R by Johns Hopkins University
- Specialization: Genomic Data Science by Johns Hopkins University
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Hamidou Sy (verified owner) –
Eko Subagyo (verified owner) –
Jan Willem (verified owner) –
Some helpful recipes to get you started quickly. It lacks clear explanation on background and no description about other function attributes. Delivered promptly.
Oscar Salas (verified owner) –
Rita L. (verified owner) –
Christian Larsen (verified owner) –
clear concise examples. I found the code to be very useful to accelerate progress for my closely related projects.
A more in-depth follow up on book would be interesting. Also I’d love to see an R connection to neo4j graph databases