CSE416A ANALYSIS OF NETWORK DATA Fall 2019 Marion Neumann SEMESTER SUMMARY Contents in these slides may be subject to copyright. Some materials are adopted from: http://www.cs.cornell.edu/home/kleinber/networks-book, http://web.stanford.edu/class/cs224w/ , http://www.mmds.org .
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CSE416A ANALYSIS OF NETWORK DATA
Fall 2019Marion Neumann
SEMESTER SUMMARY
Contents in these slides may be subject to copyright. Some materials are adopted from: http://www.cs.cornell.edu/home/kleinber/networks-book, http://web.stanford.edu/class/cs224w/, http://www.mmds.org.
• What do we study in networks? • Structure and evolution:• What is the structure of a network? • Why and how did it become to have such structure?
• Processes and dynamics: • networks provide “skeleton” for spreading of information,
behavior, diseases, …
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REASONING ABOUT NETWORKS
• How do we reason about/understand networks? • Empirical: Study network data to find organizational
principles• Mathematical models: Study probabilistic models
and graph theory to derive properties theoretically• Algorithms: Methods for analyzing graphs to
compute patterns, similarities, and interesting hidden features
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REASONING ABOUT NETWORKS• Empirical à organizational principles• Mathematical models à theoretical properties• Algorithms à patterns, similarities, features
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Mathematics à prob/statsà graph theory à linear algebra
Field of Application
à social/political science
à biologyà intelligenceà ...
Computer Science
à algorithms & data structures
à data scienceà big data
Structure and Evolution
Processes and Dynamics
WHAT WE LEARNED 1. Communities in Networks2. Betweenness-based Clustering
Complex Network Analysis: Use empirical measures, comparisons to network models, and network algorithms to reasonabout network properties and underlying phenomena.
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map of superpowers
SUMMARY
• You have learned a lot!• answered insightful questions• derived many interesting results • implemented a number of algorithms• practiced many real-world workflows