Text Mining and Citation Network of Ecosystem Services Publications

Ecosystem Services is an important concept to achieve Sustainable Development Goals 2030. For the past 20 years, this concept has grown exponentially and the metadata of these publications can be considered as big data. A bibliometric analysis was conducted to Ecosystem Services publications from Web of Science database, which are text-mining analysis, bibliographic coupling, and citation network analysis. Text-mining analysis results were a cluster map of keywords representing the content of abstract and title from 4203 publications in the dataset. Bibliographic coupling analysis results were a cluster of documents which analyzed using natural language processing to extract the main idea of the documents. Using these two analysis insight about ecosystem services are obtained. Ecosystem services in general can be divided into 6 big clusters: economic assessment of ecosystem services as natural capital, ecosystem services assessment in term of accounting and management, biodiversity conservation in term of species richness, biodiversity conservation in term of human well-being, climate change and ecosystem services, and ecosystem services in urban area. Finally, citation network analysis was performed. 5700 publications consist of publications from the dataset and cited references from the publications were analyzed and 50 most influential articles from 1977 to 2018 with highest citation score was plotted in chronological order, providing insight on how the topic has been developing over time and important publications to be read. Bibliometric analysis proved to be very useful, especially as the preliminary step before conducting literature review. This technique can be very beneficial for early career scientists who wanted to recognize a field of science or wanted to know the research gaps that could be worked on.