Latent Dirichlet Allocation-based method and Cosine Similarity: Aligning Research Publications with the United Nations’ Sustainable Development Goals
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- Master of Science 
According to the United Nations Statistics Division (2021) the development of the Sustainable Development Goals is running behind schedule. Higher education plays a significant role in prioritising and implementing research as part of their sustainability agenda. Although there are compelling reasons for research faculty to focus research contributions on advancing the Sustainable Development Goals, current applications for identifying such efforts heavily rely on manual involvement. In order to assess how the research publications at a Norwegian business school were aligned with the Sustainable Development Goals, we investigated and implemented an SDG classifier based on Latent Dirichlet Allocation developed by LaFleur (2019). In addition, cosine similarity was used as an alternative method for identifying the most similar research publications in the corpus to the Sustainable Development Goals. Our results show that BI Norwegian Business School, has made clear contributions to the Sustainable Development Goals, when using both the SDG classifier and cosine similarity. As a result, both methods are adequate for identifying Sustainable Development Goals in research publications for our purposes. However, the SDG classifier produces more reliable results than cosine similarity as it is able to capture Sustainable Development Goals-related topics in research publications where they are not always prominent.
Masteroppgave(MSc) in Master of Science in Business Analytics - Handelshøyskolen BI, 2022