Course Summary
This course covers the key concepts of social network analysis and its applications in various fields such as business, healthcare, and social media. You will learn how to use Python and other tools to analyze social networks and gain insights into various network properties.Key Learning Points
- Understand the basic concepts and terminology of social network analysis
- Learn how to use Python and other tools for network analysis
- Apply network analysis to real-world problems in various fields
Related Topics for further study
- Social Network Analysis
- Python Programming
- Business Insights
- Healthcare Applications
- Social Media Analytics
Learning Outcomes
- Understand the fundamentals of social network analysis
- Apply network analysis to real-world problems
- Gain insights into network properties and their implications
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python programming
- Familiarity with data analysis concepts
Course Difficulty Level
IntermediateCourse Format
- Online self-paced
- Video lectures
- Hands-on coding exercises
Similar Courses
- Data Mining and Analysis
- Machine Learning
Notable People in This Field
- Duncan Watts
- Albert-László Barabási
Related Books
Description
This course is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the course, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics.
Knowledge
- Define networks and discover the languages networks use.
- Analyze a social network through data wrangling and visualizing a network.
- Discuss what mechanisms generate networks.
- Examine social networks analysis using case studies.
Outline
- Getting Started and Formalizing Networks
- What is this Specialization About?
- Course Introduction
- Social Equals Network
- Nodes
- Links
- Nodes and/or Links
- Strength of Ties
- Formalizing Networks
- About UCCSS
- A Note From UC Davis
- Module 1 Quiz
- Social Network Analysis
- Module Introduction
- Network Jargon
- Degrees
- Roaming the Network
- Communities
- Triangles
- Network Centrality (Part 1)
- Network Centrality (Part 2)
- Community Detection
- Eigenvector Centrality
- Three Kinds of Measures
- Network Analysis Software
- Optional/Complementary
- Module 2 Quiz
- Analyzing a Network with Software
- Module Introduction
- Data Wrangling
- Network Measures (Part 1)
- Network Measures (Part 2)
- Influentials
- Who's Influential?
- Twitter Cascades
- Base Rate
- Modeling Influentials
- Social Network Analysis - Getting Started
- Social Network Analysis Lab Tutorial
- Welcome to Peer Review Assignments!
- Optional/Complementary
- Module 3 Quiz
- Network Evolution
- How do Networks Evolve?
- Network Dynamics
- Network Hypotheses
- Random Graphs
- Tipping Points
- Scale-Free Networks
- Hybrid Models
- Small World Networks
- Module 4 Quiz
- Growing Networks and Making Predictions
- Module Introduction
- Growing Efficient Networks (Part 1)
- Growing Efficient Networks (Part 2)
- Growing Stable Networks
- Efficiency & Stability
- Diffusion of Network
- Diffusion Patterns
- Computing Networks
- Course Summary
- Module 5 Quiz
Summary of User Reviews
Social Network Analysis course on Coursera has received positive reviews from users. The course covers the study of networks, their properties, and how they can be analyzed. Many users praised the comprehensive approach taken by the instructor towards the subject matter.Key Aspect Users Liked About This Course
Comprehensive approach towards the subject matterPros from User Reviews
- Great explanation of concepts
- Engaging instructor
- Practical assignments
- In-depth coverage of the topic
- Easy to follow structure
Cons from User Reviews
- Some users found the course to be too technical
- Not enough emphasis on real-world applications
- Lack of interaction with other students
- Slow pace in the beginning
- No certificate of completion for the free version
Martin Hilbert
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