ASDK20015U Climate opinion and behavior in social data science

Volume 2024/2025

Elective course offered by the MSc in Social Data Science

Full-degree students enrolled at the Faculty of Social Science, UCPH

  • Master Programme in Social Data Science
  • Master Programme in Political Science
  •  Master Programme in Social Science


Enrolled students register the course through the Selfservice. Please contact the study administration at each programme for questions regarding registration.

The course is open to:

  • Exchange and Guest students from abroad

This course will cover data-driven perspectives on climate change opinion and behavior. We will mostly focus on the attitudes and behaviors of ordinary people in the global North; and we will be looking mostly at mitigation (cutting emissions) with only limited attention to adaptation (dealing with the consequences of climate change). The methods discussed in the course will be largely quantitative, with minor journeys into qualitative approaches.

We will build on students’ existing knowledge of quantitative methods, applying those methods to problems in climate social science. The focus of this course is therefore on applying methods (ranging from basic to advanced) in practice, rather than on teaching new methods. This is why the course requires a background in statistics (see course requirements).

We will investigate psychological topics such as: barriers and drivers of pro-environmental behavior, behavioral change interventions, environmental communication, gamification, and the behavioral economics of climate change. We will also cover topics from political science and sociology, including: measuring climate change opinion via polls, the effects on climate attitudes of norms and social identities, media and social media; and the causes and effects of climate movement participation.

Guest lecturers will bring in state-of-the art data science research in climate psychology and sociology.

The course will feature hands-on experience of climate behavior interventions in Virtual Reality, and analysis of the data resulting from such a VR intervention.

Learning Outcome


- know how to measure climate change attitudes and behaviors

- know what are the main correlates and drivers of these attitudes and behaviors

- know what are the main approaches to promoting pro-environmental behavior

- be able to discuss climate attitudes and behaviors from a psychological, political and sociological perspective



- be able to apply the tools and methods we use in the study of climate psychology, such as questionnaires and experiments

- be able to apply the tools and methods we use in the study of climate politics and sociology, such as observational studies



- Be able to critically read and assess state-of-the art research in behavioral science, public opinion studies, and political psychology in the area of climate change.

Berger, Sebastian, Andreas Kilchenmann, Oliver Lenz, Axel Ockenfels, Francisco Schlöder, and Annika M. Wyss. 2022. “Large but Diminishing Effects of Climate Action Nudges under Rising Costs.” Nature Human Behaviour 6 (10): 1381–85. https:/​/​​10.1038/​s41562-022-01379-7.


Bergquist M, Thiel M, Goldberg MH, et al. (2023) Field interventions for climate change mitigation behaviors: A second-order meta-analysis. Proceedings of the National Academy of Sciences of the United States of America 120(13): e2214851120.


Bergquist, Parrish, Clara Vandeweerdt, Matto Mildenberger, Peter Howe, Jennifer Marlon. Measuring global concern about climate change with a dynamic, group-level item response theory model. Working paper.


Feinberg, Matthew, and Robb Willer. "The moral roots of environmental attitudes." Psychological science 24, no. 1 (2013): 56-62. Discussion text.


Fielding, Kelly S., and Matthew J. Hornsey. "A social identity analysis of climate change and environmental attitudes and behaviors: Insights and opportunities." Frontiers in psychology 7 (2016): 121. Discussion text.


Klöckner CA (2013) A comprehensive model of the psychology of environmental behaviour—A meta-analysis. Global environmental change: human and policy dimensions 23(5). Elsevier BV: 1028–1038.


Maki, Alexander, Amanda R. Carrico, Kaitlin T. Raimi, Heather Barnes Truelove, Brandon Araujo, and Kam Leung Yeung. 2019. “Meta-Analysis of pro-Environmental Behaviour Spillover.” Nature Sustainability 2 (4): 307–15. https:/​/​​10.1038/​s41893-019-0263-9.


Mildenberger, Matto, and Dustin Tingley. "Beliefs about climate beliefs: the importance of second-order opinions for climate politics." British Journal of Political Science 49, no. 4 (2019): 1279-1307.


van Valkengoed AM, Abrahamse W and Steg L (2022) To select effective interventions for pro-environmental behaviour change, we need to consider determinants of behaviour. Nature human behaviour 6(11): 1482–1492.

Basic statistics (linear regression, ANOVA) and familiarity with at least one statistical software (e.g. R, SPSS, python) are a prerequisite.

A familiarity with applied quantitative research methods (experimental design and analysis, causality in observational studies) is strongly recommended.
Interactive lectures
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 102
  • Exam
  • 76
  • Total
  • 206
Feedback by final exam (In addition to the grade)
Peer feedback (Students give each other feedback)
7,5 ECTS
Type of assessment
Type of assessment details
The final exam will consist of 3 portfolios handed in together at the end of the course.
All aids allowed

ChatGPT and other large language model tools are permitted as a dedicated source, meaning text copied verbatim needs to be quoted, the tool cited, and generally the specific use made of them needs to be described in the submitted exam.

Marking scale
7-point grading scale
Censorship form
No external censorship

An essay, written either in a group, or indvidually, on a course pertaining to the course content and prescribed literature. The subject must be pre-approved by the course lecturer(s).

Criteria for exam assesment

The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the course.