Coding and Analyzing Open-Ended Questions in Surveys |
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| Coordinator 1 | Dr Alice Barth (University of Bonn) |
Open-ended questions, where respondents answer in their own words instead of choosing from a range of categories, can provide information on respondents’ subjective perspectives, their interpretation and understanding of concepts, or their reasons for choosing a specific response. There are a number of methodological challenges (and opportunities!) in analyzing unstructured text data, from data preparation, cleaning and coding to text mining, statistical modeling, and visualizing results.
This session aims at discussing methods for processing and analyzing responses to open-ended questions. Topics of particular interest are, for example (but not limited to)
- Using AI in coding and analyzing responses to open-ended questions
- Pre-processing unstructured text data
- Assessing the quality of responses to open-ended questions
- Statistical analysis techniques for unstructured text data (topic models, geometric data analysis, etc.)
- Complementing or contradicting results from standardized questions by using information from open-ended questions
- Using open-ended questions as a tool in survey methodology (e.g., web probing, respondent feedback on the survey process)
We are looking forward to contributions that highlight the methodological and/or substantial potential of open-ended questions in survey research.