Mark E. Dickison

Multilayer Social Networks (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate research communities, leading to the development of several independent models and methods to deal with the same set of problems. This book unifies and consolidates existing practical and theoretical knowledge on multilayer networks including data collection and analysis, modeling, and mining of multilayer social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various methods. Researchers from all areas of network analysis will learn new aspects and future directions of this emerging field.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 18. Juli 2016
• Englisch
• ISBN-13: 9781316718834
• Artikelnr.: 52858905

Autorenporträt

Mark Dickison is a Data Science Manager at Capital One, where he attempts to put his knowledge of complex systems and technical skills at the forefront of solving business problems while still finding time to stay current with theory. He has been a post-doctoral fellow at Pennsylvania State in their USP program, which supports the US Defense Threat Reduction Agency, one of the first organizations to focus on multiple network models. His research interests fall within multidisciplinary network modeling, including network formation, and epidemiological and opinion spreading, as well as data mining and machine learning.

Inhaltsangabe

1. Moving out of flatland
Part I. Models and Measures: 2. Representing multilayer social networks
3. Measuring multilayer social networks
Part II. Mining Multilayer Networks: 4. Data collection and preprocessing
5. Visualizing multilayer networks
6. Community detection
7. Edge patterns
Part III. Dynamical Processes: 8. Formation of multilayer social networks
9. Information and behavior diffusion
Part IV. Conclusion: 10. Future directions.