Bibliometric and sentiment analysis with machine learning on the scientific contribution of Professor Srinivasa Sourirajan
| dc.contributor.author | Khayet Souhaimi, Mohamed | |
| dc.contributor.author | Aytaç, Ersin | |
| dc.contributor.author | Matsuura, Takeshi | |
| dc.date.accessioned | 2026-01-12T16:20:47Z | |
| dc.date.available | 2026-01-12T16:20:47Z | |
| dc.date.issued | 2022-12 | |
| dc.description | © 2022 Elsevier B.V. Grant number 1059B191900618 | |
| dc.description.abstract | Prof. Srinivasa Sourirajan is remembered by the desalination and membrane community as the “Father of Reverse Osmosis”. He passed away at the age of 98 peacefully in his beloved city Ottawa (Canada). His legacy will be remembered by the scientific community “membrane science, membrane processes, desalination and engineering”. His research studies were not only novel, but also very creative and even visionary. He offered a priceless gift to humanity by bringing clean water to all those in need through the presentation of reverse osmosis technology together with its appropriate membranes for water treatment, including desalination. This technology has now gained worldwide interest as it is able to produce clean water at a lower cost compared to other separation processes. His scientific contribution also pioneered other research areas. He developed novel research methodologies in geophysics while in catalysis he produced unleaded gasoline to help with the smog issue. He was nominated for the Nobel Prize three times. Prof. Sourirajan had also an exceptional humanitarian attribute. He played a significant role in bringing the Indian community to Ottawa. In the present paper we apply machine learning for his extraordinary and original scientific contribution. The results reveal how influential scientist he was. | |
| dc.description.department | Depto. de Estructura de la Materia, Física Térmica y Electrónica | |
| dc.description.faculty | Fac. de Ciencias Físicas | |
| dc.description.refereed | TRUE | |
| dc.description.sponsorship | Technological Research Council of Turkey | |
| dc.description.sponsorship | Universidad Complutense de Madrid | |
| dc.description.status | pub | |
| dc.identifier.citation | Khayet, M., Aytaç, E., & Matsuura, T. (2022). Bibliometric and sentiment analysis with machine learning on the scientific contribution of Professor Srinivasa Sourirajan. Desalination, 543, 116095. | |
| dc.identifier.doi | 10.1016/j.desal.2022.116095 | |
| dc.identifier.essn | 1873-4464 | |
| dc.identifier.issn | 0011-9164 | |
| dc.identifier.officialurl | https://doi.org/10.1016/j.desal.2022.116095 | |
| dc.identifier.relatedurl | https://www.sciencedirect.com/science/article/pii/S0011916422005501 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/129933 | |
| dc.journal.title | Desalination | |
| dc.language.iso | eng | |
| dc.page.final | 116095-12 | |
| dc.page.initial | 116095-1 | |
| dc.publisher | Elsevier | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.cdu | 66 | |
| dc.subject.cdu | 66.049 | |
| dc.subject.keyword | Biblioshiny | |
| dc.subject.keyword | Exploratory Tool | |
| dc.subject.keyword | Text mining | |
| dc.subject.keyword | VADER | |
| dc.subject.keyword | Word cloud | |
| dc.subject.ucm | Ingeniería química | |
| dc.subject.unesco | 2210.19 Fenómenos de Membrana | |
| dc.title | Bibliometric and sentiment analysis with machine learning on the scientific contribution of Professor Srinivasa Sourirajan | |
| dc.type | review article | |
| dc.type.hasVersion | AM | |
| dc.volume.number | 543 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 8e32e718-0959-4e6c-9e04-891d3d43d640 | |
| relation.isAuthorOfPublication.latestForDiscovery | 8e32e718-0959-4e6c-9e04-891d3d43d640 |
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