Basu, A, Hazra, AK, Chaudhury, S et al. (2 more authors) (2021) State of the Art Research on Sustainable Use of Water Hyacinth: A Bibliometric and Text Mining Analysis. Informatics, 8 (2). 38. ISSN 2227-9709
Abstract
This study aims to present a systematic data-driven bibliometric analysis of the water hyacinth (Eichhornia crassipes) infestation problem around the globe. As many solutions are being proposed in academia for its management, mitigation, and utilization, it requires investigation through a systematic scrutinizing lens. In this study, literature records from 1977 to June 2020 concerning research on water hyacinth are taken from Scopus for text analysis. Trends in the publication of different article types, dynamics of publication, clustering, correlation, and co-authoring patterns between different countries are observed. The cluster analysis indicated four clusters viz. (i) ecological works related to species, (ii) pollutant removal process and methods, (iii) utilization of biofuels for biogas production, and (iv) modelling works. It is clear from the networking analysis that most of the publications regarding water hyacinth are from India, followed by China and the United States. Sentiment analysis with the AFINN lexicon showed that the negative sentiment towards the aquatic weed has intensified over time. An exploratory analysis was performed using a bigram network plot, depicting and outlining different important domains of water hyacinth research. Water hyacinth research has passed the pioneering phase and is now at the end of a steady growth phase or at the beginning of an acceleration phase. In this article, an overview is given for the entirety of water hyacinth research, with an indication of future trends and possibilities.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | water hyacinth; cluster analysis; sentiment analysis; text-mining; network analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number BBSRC (Biotechnology & Biological Sciences Research Council) BB/S011439/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Sep 2021 14:41 |
Last Modified: | 30 Sep 2021 14:41 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/informatics8020038 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:178621 |