Integration of large-scale community-developed causal loop diagrams: a Natural Language Processing approach to merging factors based on semantic similarity

• Published in: BMC public health Vol. 25; no. 1; pp. 923 - 9
• Main Authors: Valdivia Cabrera, Melissa, Johnstone, Michael, Hayward, Joshua, Bolton, Kristy A., Creighton, Douglas
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 08.03.2025; BioMed Central; BMC
• Subjects: Analysis; Causal inference; Causality; Child; Community; Community health services; Computational linguistics; Decision making; Health; Health problems; Humans; Language; Language processing; Local government; Mental disorders; Mental health; Methods; Natural language interfaces; Natural Language Processing; Neural networks; Obesity; Ontology; Optimization; Public health; Qualitative research; Semantic similarity; Semantics; Sentences; Sentiment analysis; Similarity; Systems thinking; Victoria; Young adults; Victoria; Australia; Semantic similarity; Systems thinking; Health; Community; Natural Language Processing
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-025-22142-3

Complex public health problems have been addressed in communities through systems thinking and participatory methods like Group Model Building (GMB) and Causal Loop Diagrams (CLDs) albeit with some challenges. This study aimed to explore the feasibility of Natural Language Processing (NLP) in simpli...