Graph Theory Approach to Automated Environmental Content Analysis: A Systematic Review on the Topic of Marine Debris

Marine debris is one of the major environmental concerns in the 21st century, owing to its impact on the ocean ecosystems, the biodiversity of marine inhabitants, and human well-being.Through the utilization of automated content analysis (ACA) and graph theory in the context of a systematic literature review (SLR), the purpose of this investigation is to comprehensively map and assess the global research landscape concerning marine trash.Leximancer was used in this study to extract semantic links among important ideas, which were then displayed as directed acyclic graphs (DAG).The research used 357 Scopus-indexed papers that were published between 2017 and 2024.Core conceptual clusters relating to microplastics, plastics, and soil were identified through the ACA method.These clusters each reflected a different aspect of marine pollution that was interrelated with the others.The utilization of graph theory enabled the identification of structural links and core nodes that were shared by several themes.These connection points might be quantified by adjacency matrices and normalized grouping was accomplished by k-means analysis.According to the findings, phrases such as "waste", "plastics", and "marine" were the most prominent notions, and they served as the foundation for study on marine debris on a worldwide scale.These findings not only contribute to the advancement of automated environmental informatics but also highlight how graph-based content analysis may be used to identify hidden patterns in scientific knowledge.Taking into account both theoretical and methodological considerations, this study have implications for academics who use computational bibliometric analysis in the field of environmental science.