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.
Social and Economic Networks: Models and Analysis
Social and Economic Networks: Models and Analysis
Instructor: Matthew O. Jackson
Sponsored by Barbados NTI
72,521 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(747 reviews)
Advanced level
Designed for those already in the industry
Flexible schedule
Approx. 29 hours
Learn at your own pace
97%
Most learners liked this course
Skills you'll gain
- Database Management
- Mathematical Modeling
- Database Management Systems
- Statistical Modeling
- Databases
- Probability
- Bayesian Network
- Bayesian Statistics
- Network Analysis
- Data Architecture
- Database Design
- Applied Mathematics
- Relational Databases
- Data Modeling
- Database Systems
- Database Theory
- Database Architecture and Administration
Details to know
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Assessments
20 assignments
Taught in English
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There are 8 modules in this course
Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions
What's included
12 videos3 readings3 assignments
Homophily, Dynamics, Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich. Erdos and Renyi Random Networks: Thresholds and Phase Transitions
What's included
11 videos3 readings3 assignments
Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formation.
What's included
12 videos3 readings4 assignments
Game Theoretic Modeling of Network Formation, The Connections Model, The Conflict between Incentives and Efficiency, Dynamics, Directed Networks, Hybrid Models of Choice and Chance.
What's included
15 videos3 readings2 assignments
Empirical Background, The Bass Model, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data.
What's included
12 videos3 readings3 assignments
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..
What's included
9 videos3 readings2 assignments
Network Games, Peer Influences: Strategic Complements and Substitutes, the Relation between Network Structure and Behavior, A Linear Quadratic Game, Repeated Interactions and Network Structures.
What's included
10 videos4 readings2 assignments
The description goes here
What's included
1 assignment
Instructor
Instructor ratings
4.9 (109 ratings)Offered by
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4.8
747 reviews
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Showing 3 of 747
YZ
5
Reviewed on Jan 11, 2025
Thanks Professor Jackson for your generosity of sharing this course on Coursera. It's an excellent start for students interested in research on social networks analysis.
SN
4
Reviewed on Jun 5, 2020
Interesting survey of modern network theory, from Erdos-Renyi random graphs, to SIS ("flu") models, and games on networks. Rather academic at times, without the rigour.
SW
5
Reviewed on Aug 8, 2016
Very good course on Social Networks, and also a hard one even for graduate level. Generally assignments are not too tough but fully understanding all the concepts take lots of extra readings.
Recommended if you're interested in Social Sciences
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