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Socio-Political Marketing

Code: 45823
Credits: 6
2026/2027
Degree programme Type Course
Political Science OP 1

Contact lecturer

Name :
Roberto Pannico
Email :
roberto.pannico@uab.cat

Teaching staff

Luis Remiro Pernia

Group languages

You can consult this information at the end of the document.

Prerequisites

Students are expected to be familiar with the content of the Public Opinion and Political Behaviour course.

Objectives

The course pursues two main objectives. First, it provides students with an advanced understanding of the key contemporary political issues that shape public opinion, political participation, and electoral behavior. Second, it explores how political actors, the media, and citizens interact with political communication. The course is intended for students who wish to deepen their understanding of the empirical analysis of political behavior while developing the skills required for advanced research or professional practice in the fields of political communication and electoral campaigns

Learning outcomes

  • CA20 (Apply advanced theoretical and methodological knowledge to applied research on political behaviour.) Apply advanced theoretical and methodological knowledge to applied research on political behaviour.
  • CA21 (Evaluate political communication strategies and ethical dilemmas in socio-political marketing.) Evaluate political communication strategies and ethical dilemmas in socio-political marketing.
  • CA22 (Communicate complex analyses in a clear way that is tailored to academic and professional audiences.) Communicate complex analyses in a clear way that is tailored to academic and professional audiences.
  • KA19 (Interpret advanced theoretical approaches to political behaviour, including affective, identity, and polarisation theories.) Interpret advanced theoretical approaches to political behaviour, including affective, identity, and polarisation theories.
  • KA20 (Define the principles of socio-political marketing and their application in campaigns and institutional communication.) Define the principles of socio-political marketing and their application in campaigns and institutional communication.
  • KA21 (Identify new sources of data and analytical strategies applied to the study of political behaviour.) Identify new sources of data and analytical strategies applied to the study of political behaviour.
  • SA15 (Apply analytical framework and design empirical analyses for the study of political behaviour and strategic communication.) Apply analytical framework and design empirical analyses for the study of political behaviour and strategic communication.

Contents

Note that exact session content and/or order may vary until the start of the course.


Part I – Contemporary Political Issues and Public Opinion

1. Populism

2. Corruption

3. Public attitudes towards European integration

4. Voting in European elections

5. Climate politics

6. Participation beyond vote



Part II – Political Communication and Electoral Competition

7. Emotions in Politics

8. Political Campaigns, Political Marketing and News Media

9. Political Campaigns in the Digital Era

10. Political Consequences of Social Media

11. Automation, Artificial Intelligence and Political Behaviour

12. Political Leadership and Personalization


LANGUAGE:

The course is taught entirely in ENGLISH.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Reading 16 0.64 CA20, CA21, KA19, KA20
Individual study 60 2.4 CA20, CA21, KA19, KA20
Presentation/discussion articles 13 0.52 CA20, CA21, CA22, KA19, KA20
Group assignment 22.5 0.9 CA20, CA21, CA22, KA20, KA21, SA15
Keynote sessions 19.5 0.78 CA20, KA19, KA20, KA21

A typical session will include:

  • A keynote session led by the instructor where the theoretical aspects of the session will be covered.
  • Student presentations and discussion of the mandatory readings for the session
  • Additional discussion of the session content.


All students are expected to read the mandatory seminar readings and prepare their contributions.


Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Active participation in class 10 7 0.28 CA21, CA22, KA19, KA20
Group assignment 25 2.5 0.1 CA20, CA21, CA22, KA20, KA21, SA15
Final exam 50 2.5 0.1 CA21, CA22, KA19, KA20, KA21
Oral presentation of compulsory readings 15 7 0.28 CA21, CA22, KA19, KA20

The continuous assessment is structured as follows:

  • Oral presentation of compulsory readings (15%).
  • Active participation in class (10%).
  • Group work (25%).
  • Final exam (50%).


In case of exam retakes, the same evaluation method described above will apply. Exam retakes will only be granted to students that have attended the first exam and have failed it.



IMPORTANT:

  • A minimum score of 5 on the final examination is required to pass the course.
  • A student will receive a "Non-assessable" grade if any of the following conditions is met:

a. the student does not take the final examination.

b. the student attends fewer than 80% of the classes.

c. the student does not participate in the group assignment AND does not give a presentation on the compulsory readings.



In the event of a student committing any irregularity that may lead to a significant variation in the grade awarded to an assessment activity, the student will be given a zero for this activity, regardless of any disciplinary process that may take place. In the event of several irregularities in assessment activities of the same subject, the student will be given a zero as the final grade for this subject.


Exams where there have been irregularities (e.g. plagiarism, unauthorized use of AI, etc.) cannot be retaken.


The unique evaluation system is not foreseen in this module.



Use of Artificial Intelligence (AI) technologies

For this module, the use of Artificial Intelligence (AI) technologies is restricted to support tasks such as searching for information and bibliographic sources, translating and linguistically correcting texts written by the student, and generating preliminary outlines or summaries, provided that these are subsequently reworked by the student. It is not permitted to use AI to write entire texts, develop main arguments, or produce answers in individual assessment activities (exams, essays, final papers, or other main learning evidence). The student must explicitly indicate which parts of the work have been generated or assisted by AI, specify the tools used, and include a critical reflection on how these tools have influenced the process and the final result. Lack of transparency in the use of these technologies will be considered a breach of academic honesty and may result in partial or full penalties in the grading of the activity, or even more severe sanctions in serious cases.



Bibliography

The syllabus contains a detailed bibliography for each lecture.

Software

NA

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE