Current Volume 8
Sustainable finance refers to the consideration of environmental, social, and governance (ESG) factors in financial decision-making. This paper proposes to create a scientometric analysis of sustainable finance with the aid of AI and text analytics. The data of the abstract and title text were extracted from a sample of 317 research articles that had been retrieved from the ProQuest database until August 22, 2023. This study applies one of the important AI methods, that is, text mining, to systematically analyze and extract knowledge from unstructured text data. The findings of the study are bifurcated into two aspects: (1) title and abstract text data and (2) author/publication-related information. Based on the title and abstract data, word frequency analysis of the most common words used in these studies is obtained through a word cloud. Opposite to these, the least common words are identified through TF-IDF. Correlations between the words were computed and shown through correlation graphs, along with additional correlations between keywords and other words. Significant themes were generated via LDA graphs for topic modeling. The second part of the results concerns author/publication-related information, such as influential authors through authors' word cloud, collaborating authors through authors' correlation graphs, the origin of countries, how many papers are published each year, the place of publications, and top journals related to sustainable finance. This study provides valuable insights into the current state of research; identifies critical trends, voids, and opportunities in sustainable finance research; and provides insight into the future of sustainable finance research.
ESG, Text Analytics, Scientometric Analysis, Wordcloud, TF-IDF
IRE Journals:
Raijo Nirmal
"Sustainable Finance and AI" Iconic Research And Engineering Journals Volume 8 Issue 11 2025 Page 992-1001
IEEE:
Raijo Nirmal
"Sustainable Finance and AI" Iconic Research And Engineering Journals, 8(11)