Social and Economic Networks: Models and Analysis

Course Feature
  • Cost
    Free
  • Provider
    Coursera
  • Certificate
    Paid Certification
  • Language
    English
  • Start Date
    No Information
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    Matthew O. Jackson
Next Course
3.0
0 Ratings
This course will explore the social and economic networks that shape human behavior. We will examine how networks form, why they exhibit certain patterns, and how their structure impacts 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. Through this course, you will gain an understanding of the models and techniques used to analyze social and economic networks, and how they can be used to understand and predict human behavior.
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Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [May 30th, 2023]

Learning this course can help users gain a better understanding of social and economic networks and their impact on human behavior. It can provide users with the knowledge and skills to model social and economic networks, and to analyze the structure and dynamics of these networks. This course can also help users develop a deeper understanding of the various models of network formation and behavior, and how these models can be applied to real-world problems.

Possible development paths in career or education include data science, economics, sociology, mathematics, physics, statistics, and computer science. Related learning suggestions include courses in network science, machine learning, game theory, and optimization. Additionally, users can explore topics such as network analysis, network visualization, network dynamics, and network optimization. Finally, users can also look into the application of network models to real-world problems, such as the spread of diseases, the diffusion of information, and the formation of social and economic networks.

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Pros & Cons
  • Motivating lectures
  • Clear explanations
  • Well structured course
  • Length of course
  • Complex mathematics
  • Requires quantitative background
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