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Applied Mathematics

  • Teacher(s):   B.Dogan  
  • Course given in: English
  • ECTS Credits: 1.5 credits
  • Schedule: Autumn Semester 2021-2022, 1.0h. course (weekly average)
  •  sessions
  • site web du cours course website
  • Related programme: Master of Science (MSc) in Economics
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Objectives

In this course, we will cover basic mathematical tools to understand and analyze economic and social networks. First, you will learn how to represent networks (nodes, edges, paths, cycles, components of a network, degree and network density). Then, you will learn to measure networks (degree distribution, centrality, clustering). On our way, we will touch upon several economic applications, where understanding the network structure is crucial in understanding the social and economic outcomes.



Contents

  1. Basic concepts in graph theory.
  2. Basic concepts in networks.
  3. Strategic network formation.
  4. Measuring networks: degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, overall and average clustering, diameters, small worlds.
  5. Random graphs.
  6. Bipartite graphs and matching.

References

Jackson, ”Social and Economic Networks”, Princeton University Press, 2008.

West, ”Introduction to Graph Theory”, Prentice Hall, 1996.

Evaluation

First attempt

Exam:
Written 2h00 hours
Documentation:
Not allowed
Calculator:
Allowed with restrictions
Evaluation:

Your final grade will be determined by a final exam, which is written and closed-book. The duration of the final exam is 2 hours.

Retake

Exam:
Written 2h00 hours
Documentation:
Not allowed
Calculator:
Allowed with restrictions
Evaluation:

Written and closed-book.



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