ESRA 2027 sessions by theme

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Many countries have a set of well-established longitudinal survey programs, but surveys are plagued with fundamental challenges related to validity, cost, and sustainability. At the same time, technological innovations enable using new data sources, establishing new forms of data acquisition and exploring new ways to analyze this data. Far-sighted, highly interdisciplinary social science research is needed to unlock the potential of recent technological advances--particularly the boom in artificial intelligence--and to explore new forms of data, new methods of data acquisition and analysis, and new measures of data quality, in order to innovate established data spaces and integrate them with new data spaces. To achieve these goals, the German Research Foundation (DFG) has launched the Infrastructure Priority Program “New Data Spaces for the Social Sciences” (https://www.new-data-spaces.de/en-us/). In 2024, the first cohort of fifteen highly innovative research projects was funded within this program, which target four main research areas: exploration and integration of different data types, respondent-driven designs, instrument validity, and multimodal data acquisition.
The aim of this session is to present selected results of these research projects, with a particular focus on the use and applicability of AI. Topics include new perspectives on natural language processing in big data, the integration of digital trace data into surveys, new forms of interviewing and data collection--such as using avatars in virtual interview settings or capturing children’s visual perceptions from their own perspective-- machine learning and AI-enhanced validation of survey instruments, using human web traces to predict personality and knowledge, or capturing immediate reactions to societal events. The projects do not only present new developments based on the use of AI and ML in survey research but also provide findings on the impact of these innovations on data quality.