Books

I enjoy reading and learning about Network Science and Social Network Analysis. This page exists to keep a running list of what I am reading and hoping to read. There are two parts to this page: books I’ve found useful, and books I own and hope to eventually find time to read. I’m not going to review them on this page. I may occasionally talk about them in articles.

Books I’ve Found Useful

Obviously, I think you should read my book:

• Network Science with Python (Knickerbocker)

And these are the books that I learned from and/or was inspired by:

• Linked (Albert-László Barabási)

• Network Science (Albert-László Barabási)

• Sync (Steven Strogatz)

• Complex Network Analysis (Zinoviev)

• Social Network Analysis (Yang, Keller, Zheng)

• Analyzing Social Networks (Borgatti, Everett, Johnson)

• Egocentric Network Analysis (Perry, Pescosolido, Borgatti)

• Networks (Newman)

• Graph Machine Learning (Stamile, Marzullo, Deusebio)

Network Analysis and NLP go together:

• Natural Language Processing with Python (Bird)

• Natural Language Processing in Action (Lane, Hapke, Howard)

• Mastering spaCy (Altinok)

• Text as Data (Grimmer, Roberts, Stewart)

Books I Own and Hope to Read

I’ve read parts of all of these, but not enough to have found them useful, yet. If I spend more time reading these books, I’m sure I will find them useful.

• Graph Analysis and Visualization (Brath, Jonker)

• Social and Economic Networks (Jackson)

• The Practitioner’s Guide to Graph Data (Gosnell, Broecheler)

• Networks and Religion (Everton)

• Understanding Dark Networks (Cunningham, Everton, Murphy)

• Disrupting Dark Networks (Everton)

• Multilayer Networks (Bianconi)

• Network Flows (Ahuja, Magnanti, Orlin)

• Knowledge Graphs (Kejriwal, Knoblock, Szekely)

What Books Helped You?

If you have other books that you recommend, do add them in the comments!