Networks: Insights into Complex Systems and Social Structures - Mark Newman

Explore the fascinating world of network science in this lecture by SFI External Professor Mark Newman. Discover how network analysis can reveal hidden community leaders, predict voting patterns, and optimize transportation systems. Delve into key concepts such as closeness centrality, the structure of the Internet, and Google's PageRank algorithm. Examine the principles of transitivity, homophily, and modularity, and their applications in real-world scenarios. Learn how network science can be applied to diverse subjects, from social structures to the World Wide Web, and even bottlenose dolphin communities. Gain insights into the predictive power of network analysis and its statistical foundations. Enhance your understanding of complex systems through this comprehensive exploration of network theory and its practical implications.

Introduction
What are networks
closeness sensualities
how many people know
the Internet
Network Scores
Google
Transitivity
Mutual Friends
Homophony
World Wide Web Example
Prediction
Statistics
Modularity
Bottlenose Dolphins
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