Comparative Analysis of Natural Language Models Regarding Sustainable Development Goals

Developing NLP models to classify texts into the United Nations Sustainable Development Goals (SDGs) is one of the popular research inquires thanks to the the power of large language models. By leveraging advanced computational techniques, these models enable us to decipher the underlying themes and intentions within texts. They provide valuable insights into how any given text align with the diverse objectives of sustainable development. From commercial services to research institutions, we observe that there are many studies which aim to develop natural language models which are trained on SDG classification task. Even though the aims of these models are the same, previous literature shows that their results are not aligned. In this study, we aim to propose a comparative study between these models while we investigate some of the selected models at a deeper level. Ultimately, we plan to propose an answer for the difference between these models.