SODA Lab @ ESRA 2025: Emerging Topics in Survey Methodology

SODA Lab at the 11th ESRA Conference

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Members of the SODA Lab attended the 11th Conference of the European Survey Research Association (ESRA) in Utrecht, Netherlands (July 15-19, 2025), presenting on topics ranging from large language models to survey data integration.

Their contributions covered a wide range of emerging topics in survey methodology. We thank all presenters for their outstanding work and are proud to have contributed to Europe's premier forum of survey research.

All presentation materials - including abstracts, slides, and posters - are available upon request.

1. Coding and Analyzing Open-Ended Questions in Surveys

Tell me why (AIn’t nothing but a survey)? Using Large Language Models for Coding Open-Ended Survey Responses
(Link)
Leah von der Heyde (LMU Munich, Munich Center for Machine Learning) - Presenting Author
Anna-Carolina Haensch (LMU Munich, University of Maryland)
Bernd Weiß (GESIS – Leibniz Institute for the Social Sciences)

2. Data Skills for Analysts in Contemporary Social Survey Research

ASSURED. A training and accreditation service for safe research
(Link)
Dr Deb Wiltshire (GESIS-Leibniz Institute for the Social Sciences) - Presenting Author
Dr Wiebke Weber (LMU)
Dr Simon Parker (DKFZ)
Dr Vanessa Gonzalez Ribao (DKFZ)
Mr Markus Herklotz (LMU)

3. Developing Innovative and Model-Based Interventions to Combat Survey Satisficing

Evaluating methods to prevent and detect inattentive respondents in web surveys
(Link)
Lukas Olbrich (IAB Nuremberg) - Presenting Author
Joseph W. Sakshaug (IAB Nuremberg, LMU Munich, University of Mannheim)
Eric Lewandowski (NYU)

4. Measurement and Coding of Job-related Information: Occupation, Industry, and Skill

Session Organisers:
Dr Malte Schierholz (LMU Munich)
Ms Olga Kononykhina (LMU Munich / Munich Center for Machine Learning (MCML))
Dr Calvin Ge (TNO)

Can Large Language Models Advance Occupational Coding? Evidence and Methodological Insights
(Link)
Mrs Olga Kononykhina (LMU Munich / Munich Center for Machine Learning (MCML)) - Presenting Author
Dr Malte Schierholz (LMU Munich)

5. Synthetic Data Generation and Imputation with LLMs

United in Diversity? Contextual Biases in LLM-Based Predictions of the 2024 European Parliament Elections
Link

Dr des Leah von der Heyde (LMU Munich, Munich Center for Machine Learning) - Presenting Author
Dr Anna-Carolina Haensch (LMU Munich, University of Maryland)
Dr Alexander Wenz (University of Mannheim, Mannheim Centre for European Social Research)
Bolei Ma (LMU Munich, Munich Center for Machine Learning)