Game-theoretic approach to social network analysis
General data
Course ID: | 1000-2M14TGS |
Erasmus code / ISCED: |
11.3
|
Course title: | Game-theoretic approach to social network analysis |
Name in Polish: | Teorio-growe podejście do analizy sieci spolecznych |
Organizational unit: | Faculty of Mathematics, Informatics, and Mechanics |
Course groups: |
(in Polish) Przedmioty obieralne na studiach drugiego stopnia na kierunku bioinformatyka Elective courses for Computer Science Elective courses for Machine Learning |
ECTS credit allocation (and other scores): |
6.00
|
Language: | English |
Type of course: | elective monographs |
Short description: |
The course is for those interested in method of analysing social networks, including such services as Facebook or Twitter. Social network analysis (SNA) is the set of methods, tools and techniques to study groups (be them groups of local communities, customers, employees of a company, members of a tribe, animals in a herd, etc.) The key idea behind SNA is to reveal and study a complex structure of the group by considering bilateral relationships between its members. While the SNA lays at the interface of mathematics, sociology, anthropology, statistics, economics, etc.), many of its recent advancements are due to a widespread application of game theoretic models to the study of networks. |
Full description: |
During the lecture we will discuss a choice of key topics related to social network analysis and the game-theoretic approaches to social network analysis, including: - conventional and advanced centrality measures, including game-theoretic network centrality measures - dynamic changes to the network, link prediction - network creation - viral and referral marketing, influence propagation in networks - community detection and analysis in networks - criminal and terrorist network analysis |
Bibliography: |
Sanjeev Goyal. Connections: An Introduction to the Economics of Networks. Princeton University Press, Princeton and Oxford, 2007. Matthew O. Jackson. Social and Economic Networks. Princeton University Press, Princeton and Oxford, 2008. |
Learning outcomes: |
Knowledge: 1. General knowledge about game theory and network theory 2. Knowledge of fundamental methods of network analysis 3. Knowledge of fundamental and advanced game-theoretic approaches to social network analysis 4. Knowledge of fundamental research challenges in the field Skills: 1. Ability to analyse networks with key statistics and methods 2. Ability to analyse networks using game-theoretic methods and models 3. Ability to propose and apply own method (which is at least a compound of known methods) 4. Ability to assess whether a game-theoretic approach to a given problem is correct Competences 1. Awareness of the limits of the knowledge learned and of the need for further studies |
Assessment methods and assessment criteria: |
Assessment criteria for laboratories: 1. Attendance - maximum 2 unexcused absences (neccessary condition) and 2. At least 2 presentations - 90% of the final grade and 3. Quizzes and activity in class discussions - 10% of the final score Passing the lecture/course with grade: exam (there is a possibility of exemption from the exam for those who will be satisfied with the grade from laboratories and will want to have such a final grade for the entire course. If you take the exam, including the zero exam, your final grade will be the exam grade, even if it is lower than the laboratories grade). The form of the exam: written exam at home, open-ended questions, duration 2 hours, photos of solutions immediatelly sent by e-mail after the exam. Zero examination: same form of examination as above |
Classes in period "Summer semester 2023/24" (in progress)
Time span: | 2024-02-19 - 2024-06-16 |
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MO TU WYK
CW
W CW
TH FR |
Type of class: |
Classes, 30 hours
Lecture, 30 hours
|
|
Coordinators: | Tomasz Michalak | |
Group instructors: | Tomasz Michalak, Marcin Waniek | |
Students list: | (inaccessible to you) | |
Examination: | Examination |
Classes in period "Winter semester 2024/25" (future)
Time span: | 2024-10-01 - 2025-01-26 |
Navigate to timetable
MO TU W TH FR |
Type of class: |
Classes, 30 hours
Lecture, 30 hours
|
|
Coordinators: | Tomasz Michalak | |
Group instructors: | Tomasz Michalak, Marcin Waniek | |
Students list: | (inaccessible to you) | |
Examination: | Examination |
Copyright by University of Warsaw.