| To effectively monitor academic progress towards United Nations Sustainable Development Goals (SDGs), accurate and up-to-date information is crucial.Thematic modeling with keyword-based queries have emerged as a promising tool for clustering the large amounts of publications available in academic research databases.However, the effectiveness of these bibliometric queries depends on the choice of keywords used, and there is no standardized set of keywords for tracking academic progress towards the SDGs.In this study, we performed a comparative analysis of the most used keyword-based queries, assessing their advantages and disadvantages, and identifying gaps and redundancies. Based on our findings, we performed a meta-based approach to develop a new set of keywords that is both concise and thematically representative. |
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