Checking date: 15/07/2023

Course: 2023/2024

Foundations of Computational Social Science
Master in Computational Social Science (Plan: 472 - Estudio: 375)

Coordinating teacher: SANCHEZ SANCHEZ, ANGEL

Department assigned to the subject: Mathematics Department

Type: Compulsory
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
Introduction to Programming with R (19151) Basic Statistics (19152)
- Ability to understand and identify the new challenges faced by the Social Sciences in the digital world.
Skills and learning outcomes
Description of contents: programme
1. Introduction - What is computational social science (CSS)? - The paradigm of CSS - First examples - Society as a complex adaptive system - Main areas of CSS 2. Big data - Automatic information extraction and data mining - Analysis techniques - Examples 3. Social networks - Complex networks: basic definitions - Quantitative network analysis and software - Examples 4. Social complexity - Fundamentals and characteristics - Quantitative indicators - Laws of social complexity 5. Models and simulations - Model construction - The purpose of simulations - Basic software: NetLogo - Examples
Learning activities and methodology
Training Activities: - Theoretical classes - Theoretical-practical classes - Tutorials - Group work - Individual student work Teaching Methods: - Presentations in the professor's lecture room with computer and audiovisual support, in which the main concepts of the subject are developed and a bibliography is provided to complement the students' learning. - Critical reading of texts recommended by the subject professor: Press articles, reports, manuals and/or academic articles, either for later discussion in class, or to expand and consolidate knowledge of the subject. - Presentation and discussion in class, under the moderation of the professor, of topics related to the content of the subject, as well as practical case studies. - Developing pieces of work and reports, individually or in group. - Seminars/lectures by national and international experts, in face-to-face or remote synchronous sessions.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Basic Bibliography
  • Claudio Cioffi-Revilla. Introduction to Computational Social Science: Principles and Applications. Springer. 2017

The course syllabus may change due academic events or other reasons.

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