This course, "Social Network Analysis," offered by the University of California, Davis, delves into the science of social networks, offering a comprehensive understanding of their structure and dynamics. The course equips students with the knowledge and tools to analyze, visualize, and predict network behavior, making it ideal for individuals interested in computational and social sciences.
The course covers a range of topics, from formalizing networks and analyzing social networks through data wrangling to examining network evolution and making predictions. Through hands-on labs and case studies, students will gain practical experience in visualizing and analyzing networks using software.
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This course consists of five modules that cover a range of topics, including formalizing networks, social network analysis, analyzing networks with software, network evolution, and making predictions. Students will gain practical experience and knowledge to understand and predict network behavior.
This module, "Getting Started and Formalizing Networks," offers an introduction to the course and the fundamental concepts of formalizing networks. Students will learn about nodes, links, strength of ties, and other essential elements of network structure. The module includes a quiz to assess understanding and learning goals to reinforce key concepts.
The "Social Network Analysis" module delves into network jargon, degrees, network centrality, communities, and network analysis software. It provides a comprehensive understanding of social network analysis, including visualization and analysis of networks. The module also includes a quiz to test comprehension.
In the "Analyzing a Network with Software" module, students will gain practical experience in data wrangling, visualizing networks, and analyzing network measures. The module includes a lab tutorial, peer review assignments, and a quiz to assess understanding.
The "Network Evolution" module explores how networks evolve over time, including network dynamics, hypotheses, random graphs, and small world networks. Students will gain insights into the dynamics of network evolution and take a quiz to reinforce their understanding.
The "Growing Networks and Making Predictions" module focuses on growing efficient and stable networks, diffusion patterns, and computing networks. It concludes with a course summary, allowing students to reflect on their learning. The module also includes a quiz to test comprehension.
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