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Course module: 202001047
202001047
Web Science Final Project
Course info
Course module202001047
Credits (ECTS)2
Course typeStudy Unit
Language of instructionEnglish
Contact persondr.ir. M.J. van Sinderen
E-mailm.j.vansinderen@utwente.nl
Lecturer(s)
PreviousNext 3
Examiner
N. Bouali
Examiner
dr. D. Bucur
Examiner
dr. F.A. Bukhsh
Lecturer
dr.ir. M. de Graaf
Examiner
dr. D.V. Le Viet Duc
Academic year2021
Starting block
1B
RemarksB-TCS students register via Osiris; others contact modulesupport-tcs@utwente.nl. Minor students: register for the minor!
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Aims
Learning goal is to be able to  recognize and explain network phenomena. Social networks such as Facebook, information networks such as the Web, and institutions such as voting are all IT-enabled. The student will learn:
  • how to recognize and explain structural and dynamic phenomena in these networks, such as cascading behavior and power laws, and
  • how to model and analyze using graph theory and game theory.
After following this module, the student is able to:
  • Recognize these phenomena in practice;
  • Apply mathematical models from graph theory, probability, and game theory to describe and analyze them;
  • Explain and predict network phenomena in terms of network structure and behavior;
  • Operationalize and apply these models to existing network data.
In this study unit of the module Web Science we focus on one specific topic, in order to deepen practical knowledge and skills regarding this topic.
 
Content
Students will work in small groups on an assignment related to one of the following topics: graphs and social networks, information networks, network dynamics, game theory and network traffic, auctions and matching markets, and institutions and aggregate behaviour. There are several assignments to choose from, but each assignment can only be chosen by a limited number of groups.
Each assignment requires to study a topic from the book in more depth, typically using supplementary material that is provided by the teachers or has to be acquired by a literature search. The supplementary material could include data sets that have to be analyzed.
The results of the study have to be reported in an essay, and orally presented to the teachers and the peer groups.
 
Assumed previous knowledge
Some experience with programming, specifically Python.
Module
Module 8D
Participating study
Bachelor Technical Computer Science
Required materials
Book
David Easley and Jon Kleinberg, Networks, Crowds, and Markets: Reasoning About a Highly Connected World. ISBN: 978-0-521-19533-1. The book can be downloaded from http://www.cs.cornell.edu/home/kleinber/networks-book/.
Recommended materials
Course material
Supplementary material (articles, data sets)
Instructional modes
Presentation(s)
Presence dutyYes

Project unsupervised
Presence dutyYes

Tests
Deepening Practical Knowledge and Skills

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Kies de Nederlandse taal