AI Solutions to Better Use Textual Qualitative Survey Data

Leader: Krista Lagus, University of Helsinki/SOC; Partners: CSC, JYU, UEF; Collaborators: UTU, TAU

The foreseen impact is to provide infrastructure that enables better use of textual qualitative survey data that is a basic method for data collection in SSH. We currently have tools to analyse large-scale numeric survey data, but we also need tools to analyse unstructured qualitative textual data in Finnish surveys. Especially in large datasets with thousands of respondents such textual data is laborious to analyse without computer-assisted tools. We will deliver a software package for the discovery of a network of related concepts from unstructured texts in Finnish, using a combination of AI and human input and a preliminary user interface for browsing and searching the results. The reliability of the developed solution is assessed through pilot studies using the existing datasets from the Centre of Excellence in Research on Ageing and Care (JYU)