Checking date: 25/11/2021

Course: 2024/2025

Applied Political Inteligence
Bachelor in Political Science (Plan: 396 - Estudio: 205)

Coordinating teacher: LORENZO RODRIGUEZ, JAVIER

Department assigned to the subject: Social Sciences Department

Type: Electives
ECTS Credits: 6.0 ECTS


Requirements (Subjects that are assumed to be known)
Research Methodology in Social Sciences Statistics applied to the Social Sciences I and II Theories and Research Approaches in Political Science Comparative Politics I Political Behaviour Research Techniques in Political Science Electoral Analysis
To introduce the fundamental concepts of Political Intelligence, Big Data and Computational Science applied to Political Science. To understand the implications of these new techniques in the study of political and social behaviour. To understand the implications of the basic techniques of Computational Science applied to the study of Political Science.
Skills and learning outcomes
Description of contents: programme
- Introduction to Political Intelligence - Concept of Intelligence and Political Intelligence - Big Data and Artificial Intelligence - Definition, concept and main differences with other "neighbouring" concepts - Application of Political Intelligence to political problems - Political and electoral behaviour - Marketing and political communication - Public policy - Security policies - Disinformation, hoaxes - Privacy and ethical issues - Applied political intelligence techniques - Theoretical and methodological implications: correlation vs. causation - Data collection techniques - Storage platforms and software for information processing - Use of basic quantitative methods for intelligence analysis - Visualisation techniques - Introduction to foresight and future studies
Learning activities and methodology
The lecture sessions are a combination of lectures and discussions of the content of the course readings. Students should be prepared to take notes on the lectures and participate in discussions of the readings. The seminar classes consist of exploring platforms and software associated with the subject matter of the unit, and carrying out tasks, exercises and assignments using some of the techniques or software shown. The course is structured into 4 established and compulsory activities in order to pass the course. 1) Active participation in the tasks and discussions in the lectures and seminars classes.¿2) Group research work.¿3) Hand in different exercises proposed throughout the course. 4) Final exam
Assessment System
  • % end-of-term-examination 40
  • % of continuous assessment (assigments, laboratory, practicals...) 60

Calendar of Continuous assessment

Extraordinary call: regulations
Basic Bibliography
  • Barreiro, B.. La sociedad que seremos¿: digitales, analógicos, acomodados y empobrecidos.. Planeta. 2017
  • González-Bailón, Sandra.. Decoding the Social World: Data Science and the Unintended Consequences of Communication. The MIT Press. 2017
  • Jungherr, A., Rivero, G., & Gayo-Avello, D. Retooling Politics: How Digital Media Are Shaping Democracy. Cambridge University Press. 2020
  • Persily, N., & Tucker, J.. Social Media and Democracy: The State of the Field, Prospects for Reform. Cambridge University Press. 2020
  • Robles, José Manuel; Rodríguez, J. Tinguaro; Caballero, Rafael; Gómez, Daniel . Big data para científicos sociales. Una introducción. Cuadernos Metodológicos CIS. 2020
  • Stroud, Natalie Jomini, and Shannon C. McGregor. Digital Discussions¿: How Big Data Informs Political Communication. Routledge. 2021
  • Sunstein, C. R. . Paidós Estado y Sociedad. 2003
  • Tucker, J., Guess, A., Barbera, P., Vaccari, C., Siegel, A., Sanovich, S., Stukal, D., & Nyhan, B. Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature.. SSRN Electronic Journal. 2018

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