This chapter introduced affiliation networks and the tools provided by NetworkX for working with affiliation networks, with special attention to using projections to create co-affiliation networks. Affiliation networks are ubiquitous in network data. Whenever there is a symmetrical relationship that can connect more than two things, there is an underlying affiliation structure. Many single-mode networks are really co-affiliation networks—projections of affiliation networks onto one type of node. Different projections have different interpretations, such as the number of paths or similarities. Choosing an appropriate projection for the data and for the question being asked can reveal important properties of a network that might otherwise be overlooked. Even as you encounter standard single-mode networks in the rest of this book, and in real-world data, it is often...
- Tech Categories
- Best Sellers
- New Releases
- Books
- Videos
- Audiobooks
Tech Categories Popular Audiobooks
- Articles
- Newsletters
- Free Learning
You're reading from Network Science with Python and NetworkX Quick Start Guide
Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
Read more about Edward L. Platt
Unlock this book and the full library FREE for 7 days
Author (1)
Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
Read more about Edward L. Platt