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 IEM UEM Group
72,425 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(746 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 Systems
- Database Architecture and Administration
- Database Design
- Bayesian Statistics
- Statistical Modeling
- Probability
- Bayesian Network
- Relational Databases
- Databases
- Applied Mathematics
- Database Theory
- Data Architecture
- Network Analysis
- Database Management
- Database Systems
- Data Modeling
- Mathematical Modeling
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
746 reviews
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Showing 3 of 746
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.
NG
5
Reviewed on May 16, 2023
Matthew is a very good teacher. I felt like conversating on social behaviors and network structures while learning pretty complex statistical physics.
AJ
5
Reviewed on Sep 6, 2020
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.
Recommended if you're interested in Social Sciences
University of Illinois Urbana-Champaign
University of Pennsylvania
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