This policy brief highlights the advantages of using Text Mining (TM) to enhance the analysis of public policies. TM enables the efficient analysis of large volumes of policy documents, helping to identify trends, key issues and the potential impacts of policy decisions. The FOSSR project will play a crucial role in evaluating and analyzing policies, including in the context of Science, Technology, and Innovation (STI). By integrating innovative tools, data, services and methods, FOSSR aims to enhance research practices and policy evaluation. Applying advanced analytical techniques such as machine learning, network science, and knowledge representation through the construction of ontologies, text mining within the FOSSR project will help explore and uncover hidden relationships within large textual corpora. In this policy brief, we demonstrate the potential of Text Mining in the STI context by addressing the following thematic questions: 1) can text mining help evaluate the alignment of R&D funding policies with Sustainable Development Goals (SDGs)? 2) can text mining track trends over time in environmental and societal themes within research topics? Stakeholders are encouraged to explore Text Mining as a powerful tool to enhance evaluation processes across various sectors. By adopting TM techniques, institutions can gain deeper insights in their evaluations, leading to more data-driven decision-making and improved outcomes.