Mapping the research on aquaculture. A bibliometric analysis of aquaculture literature
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Research on aquaculture is expanding along with the exceptional growth of the sector and has an important role in supporting even further the future developments of this relatively young food production industry. In this paper we examined the aquaculture literature using bibliometrics and computational semantics methods (latent semantic analysis, topic model and co-citation analysis) to identify the main themes and trends in research. We analysed bibliographic information and abstracts of 14,308 scientific articles on aquaculture recorded in Scopus. Both the latent semantic analysis and the topic model indicate that the broad themes of research on aquaculture are related to genetics and reproduction, growth and physiology, farming systems and environment, nutrition, water quality, and health. The topic model gives an estimate of the relevance of these research themes by single articles, authors, research institutions, species and time. With the co-citation analysis it was possible to identify more specific research fronts, which are attracting high number of co-citations by the scientific community. The largest research fronts are related to probiotics, benthic sediments, genomics, integrated aquaculture and water treatment. In terms of temporal evolution, some research fronts such as probiotics, genomics, sea-lice, and environmental impacts from cage aquaculture, are still expanding while others, such as mangroves and shrimp farming, benthic sediments, are gradually losing weight. While bibliometric methods do not necessarily provide a measure of output or impact of research activities, they proved useful for mapping a research area, identifying the relevance of themes in the scientific literature and understanding how research fronts evolve and interact. By using different methodological approaches the study is taking advantage of the strengths of each method in mapping the research on aquaculture and showing in the meantime possible limitations and some directions for further improvements.
KeywordsAquaculture Bibliometrics Computational semantic Topic model Latent semantic analysis Co-citation analysis
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