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Call for Abstracts

The 12th Conference of the European Survey Research Association (ESRA) will take place from 19th to 23rd July 2027. The conference will take place jointly with WAPOR in Paris, France. 

The scientific committee is now inviting researchers who are active in the field of survey research, survey methodology and data analysis to submit proposals for individual paper and poster presentations.

To be part of the conference programme, start by selecting a suitable session for your presentation. Here is a complete overview of all sessions that are being organised.

Please submit an abstract (max. 300 words) to the session of your choice via the ESRA conference management system by 12th January 2027.

To submit an abstract, you must log in to your ESRA account (or create a new account if you do not already have one) and then follow the instructions provided. Please note that it is only possible to submit up to two abstracts as the first author/presenter.

The conference theme is ‘Moving forward: integrating survey methods, statistics and social data science with new data sources, AI, and machine learning’. We welcome submissions related to this theme, or in any other area of survey methodology, statistics or substantive area of survey research. We encourage proposals from researchers with a variety of backgrounds, including academic research, official statistics, commercial research, and government social research.

If you are an early career scholar, please consider applying for the Early Career Award. Information regarding criteria, eligibility, and evaluation process is available here. 

If you want to apply for a Travel & Stay Grant, see here.

The following conference tracks and subtracks are of particular interest, and the list of available sessions broadly covers these areas:

A) Survey methodology and survey practice

  1. Questionnaire design, testing and measurement 
  2. Online, mobile, and app-based surveys 
  3. Mixed-mode designs and mode effects
  4. Fieldwork processes, including responsive and adaptive designs
  5. Life-tracking and sensor-based data collection methods: Bluetooth technologies, near-field communication, smart surveys, and web scraping.
  6. Citizen Science
  7. Collecting biomarkers and other specimen data within surveys
  8. Analysing, monitoring and reducing Total Survey Error; using paradata to evaluate survey quality
  9. Interviewers and interviewer effects
  10. Cross-national and cross-cultural survey methods
  11. Survey experiments and causal inference
  12. Data management, processing, and open science
  13. Longitudinal survey design and analysis
  14. Proxy responses
  15. Nonresponse, survey participation, and survey climate
  16. Survey costs, value, and the economics of survey design
  17. Mixed methods: integrating qualitative and quantitative approaches
  18. Market research

B) Survey statistics

  1. Probability and non-probability sampling
  2. Spatial sampling and use of remote sensing data
  3. Missing data imputation
  4. Weighting approaches including survey calibration
  5. Small area estimation under non-probability and probability sampling
  6. Data integration methods (statistical matching and record linkage) with a particular focus on how to integrate new forms of data with traditional data sources
  7. How new forms of data can be used for population-size estimation
  8. More on post data collection processing such as coding and editing; related errors and how to take these into account
  9. Imputation approaches

C) Inclusive data collection and analysis in survey research

  1. Sampling and recruitment strategies for hard-to-reach, marginalised, and minority populations
  2. Multilingual survey design and cross-cultural questionnaire development
  3. Measuring gender identity, sexual orientation, and other diverse identities
  4. Accessibility in surveys (e.g., disabilities, digital exclusion, cognitive accessibility, literacy barriers)
  5. Ethical issues in inclusive data collection and sensitive identity measurement
  6. Participatory and community-engaged approaches to survey design and dissemination 
  7. Weighting, calibration, and adjustment methods for underrepresented populations
  8. Case studies and applications of inclusive survey methods in official statistics and social research 
  9. Survey research in conflict, crisis, and humanitarian contexts
  10. Capacity building and survey research in low-income contexts
  11. Analytical challenges with small and underrepresented subgroups

D) Data governance: documentation, archiving, and access

  1. Privacy, confidentiality and consent
  2. Data security and access
  3. Survey data harmonization: ex-ante and ex-post approaches
  4. Open data, FAIR principles, and data sharing 
  5. Reproducibility, transparency, and open science in survey research
  6. Data infrastructures and resources
  7. Data archiving, preservation, and long-term access

E) Artificial Intelligence and automated methods in survey research

  1. AI-assisted questionnaire design, translation, and pretesting
  2. Synthetic respondents and synthetic data
  3. AI interviewers and conversational survey agents
  4. Automated coding and processing of open-ended responses
  5. AI in data analysis
  6. Machine learning for weighting, imputation, and estimation
  7. AI in fieldwork management and adaptive survey operations
  8. AI in survey project management and workflow automation
  9. AI for dissemination, reporting, and public engagement with survey data
  10. Evaluating, auditing, and benchmarking AI tools in survey research
  11. Ethics, transparency, and accountability in AI-assisted survey research
  12. Bot detection and fraudulent responses in online surveys, including LLM-generated data

F) Substantive applications of survey research in the social and behavioural sciences.