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.

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

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.