Measuring University Contributions to the Sustainable Development Goals: An NLP-Based Assessment Framework

Phoebe Koundouri (), Conrad Landis, Stathis Devves, Theofanis Zacharatos and Georgios Feretzakis

No 2562, DEOS Working Papers from Athens University of Economics and Business

Abstract: Systematic assessment of university contributions to the United Nations Sustainable Development Goals (SDGs) remains challenging due to the lack of standardized, scalable evaluation frameworks. This paper introduces a comprehensive four-pillar assessment framework combining advanced natural language processing and machine learning techniques with qualitative analysis to evaluate university engagement across Research, Education, Organizational Governance, and External Leadership dimensions. We demonstrate the framework's application through an empirical case study of Athens University of Economics and Business (AUEB), analyzing 870 working papers, educational curricula, organizational policies, and partnership activities. The automated content analysis reveals strong alignment with institutional and partnership-oriented goals (SDG 16: 99% coverage, SDG 17: 95.8%), economic development goals (SDG 8: 80.7%, SDG 9: 80.1%), and gender equality (SDG 5: 81.4%), while identifying significant gaps in environmental SDGs. The framework's multi-method approach, combining zero-shot classification, semantic similarity, named entity recognition, pattern matching, and topic modeling, provides reliable and transparent assessment suitable for replication across diverse institutional contexts. This replicable methodology enables universities worldwide to systematically evaluate their SDG contributions, identify strategic priorities, and enhance accountability to sustainable development commitments.

Keywords: Sustainable Development Goals; Natural Language Processing; Machine Learning; Higher Education Assessment; University Performance Measurement; Text Mining; Semantic Analysis; Research Evaluation; Computational Social Science (search for similar items in EconPapers)
Date: 2025-11-17
New Economics Papers: this item is included in nep-big and nep-env
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