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Matthew O. Jackson
Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.
Read more
Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.
Read more
Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.
The course begins with some empirical background on social and economic networks, and an overview of concepts used to describe and measure networks. Next, we will cover a set of models of how networks form, including random network models as well as strategic formation models, and some hybrids. We will then discuss a series of models of how networks impact behavior, including contagion, diffusion, learning, and peer influences.
You can find a more detailed syllabus here: http://web.stanford.edu/~jacksonm/Networks-Online-Syllabus.pdf
You can find a short introductory videao here: http://web.stanford.edu/~jacksonm/Intro_Networks.mp4
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What's inside
Syllabus
Introduction, Empirical Background and Definitions
Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions
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Syllabus
Introduction, Empirical Background and Definitions
Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions
Read more
Background, Definitions, and Measures Continued
Homophily, Dynamics, Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich. Erdos and Renyi Random Networks: Thresholds and Phase Transitions
Random Networks
Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formation.
Strategic Network Formation
Game Theoretic Modeling of Network Formation, The Connections Model, The Conflict between Incentives and Efficiency, Dynamics, Directed Networks, Hybrid Models of Choice and Chance.
Diffusion on Networks
Empirical Background, The Bass Model, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data.
Learning on Networks
Bayesian Learning on Networks, The DeGroot Model of Learning on a Network, Convergence of Beliefs, The Wisdom of Crowds, How Influence depends on Network Position..
Games on Networks
Network Games, Peer Influences: Strategic Complements and Substitutes, the Relation between Network Structure and Behavior, A Linear Quadratic Game, Repeated Interactions and Network Structures.
Final Exam
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Good to know
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Know what's good ,
what to watch for , and
possible dealbreakers
Teaches learners how to model social and economic networks using techniques from economics, sociology, math, physics, statistics, and computer science, which prepares students for work in a range of industries
Provides a strong foundation in network modeling for beginners who want to break into social science analytics, network modeling for social science, or computer science
Matthew O. Jackson is a highly regarded professor whose work and research focus on the fields of network science and social science analytics
Covers topics such as network formation, diffusion, learning, and peer influences, which are relevant to social scientists, economists, computer scientists, and physicists alike
Offers a multi-modal learning experience with videos, readings, discussions, and hands-on labs that are relevant to current industry needs, including strategic network formation and diffusion on networks
Requires learners to have basic knowledge of probability and linear algebra, which may not be accessible to all learners
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Reviews summary
Enlightening network analysis: theories and models
Learners say this course provides a strong foundation for understanding network science and economic models. Engaging lectures, clear explanations, and real-world examples make the course suitable for both beginners and advanced learners. The course covers key concepts such as network formation, centrality measures, and game theory. Learners with a quantitative background will especially appreciate the mathematical depth of the course.
The course is accessible to beginners in network science.
"This is a fascinating and stimulating course in which I learned enough to make my brain overheat at the end of every session."
"The course is extremely well-structured and very well in-depth. The beginning is smooth and very carefully put together which makes it really interesting and hard to drop."
The course provides insights into how network models are used in the real world.
"This course opened my eyes to an entire discipline. Very interesting! Thanks"
"I'm sure this network course will give you the understanding and confidence to analyze social media successfully."
The course goes into depth with the mathematics behind network analysis.
"This course provides a solid foundation to start exploring the world of networks."
"Still, I should warn anyone interested in this course that it requires a great dose of mathematics, from linear algebra to differential calculus."
The course instructor is praised for their clarity and expertise
"Professor Jackson is amazing, the literature cited is extremely recent and lets you know that Professor Jackson is one of its main contributors."
"Dr. Jackson is clear and concise in his explanations and did a great job creating a high-level overview course on a subject for which he obviously has a much greater wealth of knowledge."
"The clarity of thought and his method of explaining even complex mathematical forms and derivations so easily by breaking them down makes the course a lot easier and interesting, even for a person who does not possess a higher level of skill in mathematics."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Social and Economic Networks: Models and Analysis with these
activities:
Review linear algebra concepts
Show steps
Strengthen your foundation in linear algebra, which is essential for understanding network models and algorithms.
Browse courses on
Linear Algebra
Show steps
-
Review concepts such as vectors, matrices, and linear transformations.
-
Solve practice problems to reinforce your understanding.
Revisit probability and statistics concepts
Show steps
Refresh your knowledge in probability and statistics, which are fundamental to understanding network behavior and modeling.
Browse courses on
Probability
Show steps
-
Review concepts such as probability distributions, random variables, and hypothesis testing.
-
Solve practice problems to strengthen your understanding.
Review 'Networks, Crowds, and Markets'
Show steps
Familiarize yourself with essential concepts in network science by reviewing this foundational text.
View
Networks, Crowds, and Markets: Reasoning about...
on Amazon
Show steps
-
Read the introduction and first chapter to gain an overview of the field.
-
Focus on chapters related to course topics, such as network formation and diffusion.
-
Take notes and highlight key concepts for future reference.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join or create a study group
Show steps
Engage with peers to discuss course material, share perspectives, and work on assignments collaboratively.
Show steps
-
Identify fellow students in the course.
-
Schedule regular meetings to discuss specific topics.
-
Actively participate in discussions and contribute to group learning.
Explore network visualizations with Gephi
Show steps
Gain hands-on experience visualizing networks by following guided tutorials on Gephi, a popular network analysis tool.
Browse courses on
Network Visualization
Show steps
-
Install Gephi and familiarize yourself with its interface.
-
Follow tutorials to import, explore, and visualize different types of networks.
-
Experiment with different visualization techniques and layouts.
Solve network analysis problems
Show steps
Deepen your understanding of network concepts by solving practice problems and exercises.
Show steps
-
Access online resources or textbooks with practice problems.
-
Regularly solve problems covering different network analysis topics.
-
Review solutions and identify areas for improvement.
Develop a network-based case study
Show steps
Apply your knowledge to a real-world scenario by developing a case study that analyzes a network-related problem.
Show steps
-
Identify a specific problem or phenomenon that can be analyzed using network concepts.
-
Collect and analyze relevant data to build a network model.
-
Apply network analysis techniques to explore the structure and dynamics of the network.
-
Draw insights and recommendations based on your analysis.
-
Present your findings in a written report or presentation.
Review linear algebra concepts
Show steps
Strengthen your foundation in linear algebra, which is essential for understanding network models and algorithms.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review concepts such as vectors, matrices, and linear transformations.
- Solve practice problems to reinforce your understanding.
Revisit probability and statistics concepts
Show steps
Refresh your knowledge in probability and statistics, which are fundamental to understanding network behavior and modeling.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Review concepts such as probability distributions, random variables, and hypothesis testing.
- Solve practice problems to strengthen your understanding.
Review 'Networks, Crowds, and Markets'
Show steps
Familiarize yourself with essential concepts in network science by reviewing this foundational text.
View
Networks, Crowds, and Markets: Reasoning about...
on Amazon
Show steps
Show steps
Show steps
- Read the introduction and first chapter to gain an overview of the field.
- Focus on chapters related to course topics, such as network formation and diffusion.
- Take notes and highlight key concepts for future reference.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join or create a study group
Show steps
Engage with peers to discuss course material, share perspectives, and work on assignments collaboratively.
Show steps
Show steps
Show steps
- Identify fellow students in the course.
- Schedule regular meetings to discuss specific topics.
- Actively participate in discussions and contribute to group learning.
Explore network visualizations with Gephi
Show steps
Gain hands-on experience visualizing networks by following guided tutorials on Gephi, a popular network analysis tool.
Browse courses on
Network Visualization
Show steps
Show steps
Show steps
- Install Gephi and familiarize yourself with its interface.
- Follow tutorials to import, explore, and visualize different types of networks.
- Experiment with different visualization techniques and layouts.
Solve network analysis problems
Show steps
Deepen your understanding of network concepts by solving practice problems and exercises.
Show steps
Show steps
Show steps
- Access online resources or textbooks with practice problems.
- Regularly solve problems covering different network analysis topics.
- Review solutions and identify areas for improvement.
Develop a network-based case study
Show steps
Apply your knowledge to a real-world scenario by developing a case study that analyzes a network-related problem.
Show steps
Show steps
Show steps
- Identify a specific problem or phenomenon that can be analyzed using network concepts.
- Collect and analyze relevant data to build a network model.
- Apply network analysis techniques to explore the structure and dynamics of the network.
- Draw insights and recommendations based on your analysis.
- Present your findings in a written report or presentation.
Career center
Learners who complete Social and Economic Networks: Models and Analysis will develop knowledge and skills
that may be useful to these careers:
Social Media Manager
Social Media Manager
A Social Media Manager develops and executes social media campaigns to promote products and services. Social Media Managers can use advanced knowledge of social and economic networks to better understand how to reach target audiences and create effective social media campaigns. This course may be of particular use to Social Media Managers interested in social media strategy or digital marketing.
Data Scientist
Data Scientist
A Data Scientist collects, analyzes, and interprets data to uncover insights and trends. Data Scientists can use advanced knowledge of social and economic networks to better understand how data can be used to improve decision-making and predict future outcomes. This course may be of particular use to Data Scientists interested in social network analysis or data mining.
Product Manager
Product Manager
A Product Manager develops and manages products from concept to launch. Product Managers can use advanced knowledge of social and economic networks to better understand customer needs and develop products that meet those needs. This course may be of particular use to Product Managers interested in product development or user experience.
Marketing Manager
Marketing Manager
A Marketing Manager develops and executes marketing campaigns to promote products and services. Marketing Managers can use advanced knowledge of social and economic networks to better understand how to reach target audiences and create effective marketing campaigns. This course may be of particular use to Marketing Managers interested in digital marketing or social media marketing.
Market Research Analyst
Market Research Analyst
A Market Research Analyst conducts surveys, analyzes data, and provides businesses with insights into customer behavior and market trends. Market Research Analysts can use advanced knowledge of social and economic networks to better understand how consumers interact with brands and products. This course may be of particular use to Market Research Analysts interested in social media marketing or consumer behavior.
Sociologist
Sociologist
A Sociologist studies society, social behavior, and social change and how they affect individuals and communities. Sociologists can use advanced knowledge of social and economic networks to better study and understand interactions, inequalities, and other factors that influence social behavior. This course may be of particular use to Sociologists interested in social psychology or social movements.
Human Resources Manager
Human Resources Manager
A Human Resources Manager oversees the human resources function of an organization. Human Resources Managers can use advanced knowledge of social and economic networks to better understand how to recruit, hire, and retain employees. This course may be of particular use to Human Resources Managers interested in talent management or employee development.
Sales Manager
Sales Manager
A Sales Manager leads and motivates sales teams to achieve sales targets. Sales Managers can use advanced knowledge of social and economic networks to better understand how to build relationships with customers and close deals. This course may be of particular use to Sales Managers interested in sales management or customer relationship management.
Business Analyst
Business Analyst
A Business Analyst identifies and analyzes business needs and develops solutions to improve efficiency and effectiveness. Business Analysts can use advanced knowledge of social and economic networks to better understand how organizations and teams can improve collaboration and communication. This course may be of particular use to Business Analysts interested in organizational development or process improvement.
Public Relations Specialist
Public Relations Specialist
A Public Relations Specialist manages the public image of organizations and individuals. Public Relations Specialists can use advanced knowledge of social and economic networks to better understand how to reach target audiences and build relationships with stakeholders. This course may be of particular use to Public Relations Specialists interested in social media management or media relations.
Consultant
Consultant
A Consultant provides advice and guidance to businesses and organizations. Consultants can use advanced knowledge of social and economic networks to better understand how to improve organizational performance. This course may be of particular use to Consultants interested in management consulting or organizational development.
Customer Success Manager
Customer Success Manager
A Customer Success Manager helps customers achieve their goals with a product or service. Customer Success Managers can use advanced knowledge of social and economic networks to better understand how to build relationships with customers and ensure their satisfaction. This course may be of particular use to Customer Success Managers interested in customer relationship management or account management.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations. Financial Analysts can use advanced knowledge of social and economic networks to better understand how economic trends and events can affect financial markets. This course may be of particular use to Financial Analysts interested in investment banking or portfolio management.
Operations Manager
Operations Manager
An Operations Manager oversees the day-to-day operations of a business. Operations Managers can use advanced knowledge of social and economic networks to better understand how to improve efficiency and effectiveness. This course may be of particular use to Operations Managers interested in process improvement or supply chain management.
Economist
Economist
An Economist analyzes data, develops theories, advises policymakers, and predicts future trends. Economists can use advanced knowledge of social and economic networks to better study and advise upon consumer behavior, supply and demand, and other factors that affect economies. This course may be of particular use to Economists interested in market research or behavioral economics.
For more career information including salaries, visit:
OpenCourser.com/course/f2aty5/social
Reading list
We've selected 15 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Social and Economic Networks: Models and Analysis.
Save
Provides a comprehensive overview of the field of social and economic networks, covering both the theoretical foundations and the latest empirical research. It is an essential resource for anyone interested in understanding how networks shape our lives.
Provides a comprehensive overview of the field of network science, covering a wide range of topics from the basics of network theory to more advanced topics such as social contagion and network games.
Provides a rigorous and accessible introduction to the theory of networks, with a focus on applications in economics, sociology, and computer science. It valuable resource for anyone interested in understanding how networks affect our social and economic lives.
Provides a comprehensive overview of the mathematical foundations of network theory. It valuable resource for anyone interested in understanding the mathematical underpinnings of social and economic networks.
Provides a detailed overview of the use of statistical mechanics to analyze complex networks, providing a more mathematically rigorous and highly technical approach to the subject matter.
Classic work on the diffusion of innovations, providing a comprehensive overview of the factors that influence how new ideas and technologies spread through society. It valuable resource for anyone interested in understanding how networks facilitate the spread of information and ideas.
Save
Provides a comprehensive overview of the field of complex networks, covering both the theoretical foundations and the latest empirical research. It valuable resource for anyone interested in understanding the structure and dynamics of complex networks.
Save
Provides a critical perspective on the impact of social networks on our lives, making it a useful resource.
Save
Provides a critical perspective on the impact of social networks on our lives, making it a useful resource.
Provides a critical perspective on the impact of social networks on our lives, making it a useful resource.
Provides a critical perspective on the impact of social networks on our lives, making it a useful resource.
Provides a critical perspective on the impact of social networks on our lives, making it a useful resource.
Save
Provides a sociological perspective on the impact of social networks on our lives, making it a useful resource.
Save
Provides a popular account of the impact of social networks on our lives, making it a useful resource.
Save
Provides a popular account of the science of networks, providing a useful introduction to the topic.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/f2aty5/social
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Stanford University
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Matthew O. Jackson
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Good to know
Teaches learners how to model social and economic networks using techniques from economics, sociology, math, physics, statistics, and computer science, which prepares students for work in a range of industries
Provides a strong foundation in network modeling for beginners who want to break into social science analytics, network modeling for social science, or computer science
Matthew O. Jackson is a highly regarded professor whose work and research focus on the fields of network science and social science analytics
Covers topics such as network formation, diffusion, learning, and peer influences, which are relevant to social scientists, economists, computer scientists, and physicists alike
Offers a multi-modal learning experience with videos, readings, discussions, and hands-on labs that are relevant to current industry needs, including strategic network formation and diffusion on networks
Requires learners to have basic knowledge of probability and linear algebra, which may not be accessible to all learners
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