Within the scope of the project, the current status and needs of textual data analysis used in social sciences were examined, and a sustainable and participatory capacity development model was created to enable researchers to use computational methods more effectively and systematically. The project aims to strengthen data-driven research culture in the social sciences through a multi-layered training package that includes introductory courses, winter and summer schools, and online sessions, as well as an artificial intelligence-supported textual analysis infrastructure to be established within the university.
Assoc. Prof. Ali ASLAN, Research Assistant Mustafa YILDIRIM, and Political Science and International Relations graduate student Tuğçe AŞAN, who are part of the project team, will play an active role in the research and training components.
This project is expected to enable researchers working in the field of social sciences to use natural language processing and machine learning-based tools more effectively, increase intra- and inter-institutional cooperation, and promote the dissemination of knowledge through open content. The model to be developed aims to standardise textual data analysis processes in universities and partner institutions; improve research quality, institutional capacity and stakeholder satisfaction; and provide a model application for decision-making mechanisms. This structure, supported by educational and laboratory outputs, is expected to contribute to the development of a more inclusive, participatory, and data-driven research culture within the university ecosystem.
