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Identifying trends in nursing start-ups using text mining of YouTube content

This study uses YouTube content to explore trends in nursing start-ups. YouTube content can be used to understand the current trends regarding interest and awareness in various fields. The study was conducted in three stages: text mining, Delphi survey, and comparison. The frequency and degree centr...

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Detalles Bibliográficos
Autores principales: Lim, Ji Young, Kim, Seulki, Kim, Juhang, Lee, Seunghwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018134/
https://www.ncbi.nlm.nih.gov/pubmed/32053627
http://dx.doi.org/10.1371/journal.pone.0226329
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author Lim, Ji Young
Kim, Seulki
Kim, Juhang
Lee, Seunghwan
author_facet Lim, Ji Young
Kim, Seulki
Kim, Juhang
Lee, Seunghwan
author_sort Lim, Ji Young
collection PubMed
description This study uses YouTube content to explore trends in nursing start-ups. YouTube content can be used to understand the current trends regarding interest and awareness in various fields. The study was conducted in three stages: text mining, Delphi survey, and comparison. The frequency and degree centrality of keywords were analyzed in the text mining stage. In the Delphi survey, the 100 most frequent keywords were classified using a synthesis framework for nursing start-ups. In the comparison stage, the results of text mining and the Delphi survey were matched using a 2x2 matrix. Text mining identified “area,” “business,” “competence,” “idea,” and “success” as the most commonly used keywords. The keywords that showed the highest level of classification agreement in Delphi were “motivation,” “advice,” “obstacle,” “business,” “charisma,” and “result.” In the comparison using a 2x2 matrix, “dream,” “idea,” “opportunity,” “leadership,” “success,” “benefit,” and “satisfaction” emerged. The results indicate that interest in nursing start-ups develops at an early stage. In order to encourage nursing start-ups, it is necessary to strengthen business skills such as finance and budgeting, establish active policy support for such start-ups, and develop new nursing start-up items appropriate for the Fourth Industrial Revolution.
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spelling pubmed-70181342020-02-26 Identifying trends in nursing start-ups using text mining of YouTube content Lim, Ji Young Kim, Seulki Kim, Juhang Lee, Seunghwan PLoS One Research Article This study uses YouTube content to explore trends in nursing start-ups. YouTube content can be used to understand the current trends regarding interest and awareness in various fields. The study was conducted in three stages: text mining, Delphi survey, and comparison. The frequency and degree centrality of keywords were analyzed in the text mining stage. In the Delphi survey, the 100 most frequent keywords were classified using a synthesis framework for nursing start-ups. In the comparison stage, the results of text mining and the Delphi survey were matched using a 2x2 matrix. Text mining identified “area,” “business,” “competence,” “idea,” and “success” as the most commonly used keywords. The keywords that showed the highest level of classification agreement in Delphi were “motivation,” “advice,” “obstacle,” “business,” “charisma,” and “result.” In the comparison using a 2x2 matrix, “dream,” “idea,” “opportunity,” “leadership,” “success,” “benefit,” and “satisfaction” emerged. The results indicate that interest in nursing start-ups develops at an early stage. In order to encourage nursing start-ups, it is necessary to strengthen business skills such as finance and budgeting, establish active policy support for such start-ups, and develop new nursing start-up items appropriate for the Fourth Industrial Revolution. Public Library of Science 2020-02-13 /pmc/articles/PMC7018134/ /pubmed/32053627 http://dx.doi.org/10.1371/journal.pone.0226329 Text en © 2020 Lim et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lim, Ji Young
Kim, Seulki
Kim, Juhang
Lee, Seunghwan
Identifying trends in nursing start-ups using text mining of YouTube content
title Identifying trends in nursing start-ups using text mining of YouTube content
title_full Identifying trends in nursing start-ups using text mining of YouTube content
title_fullStr Identifying trends in nursing start-ups using text mining of YouTube content
title_full_unstemmed Identifying trends in nursing start-ups using text mining of YouTube content
title_short Identifying trends in nursing start-ups using text mining of YouTube content
title_sort identifying trends in nursing start-ups using text mining of youtube content
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018134/
https://www.ncbi.nlm.nih.gov/pubmed/32053627
http://dx.doi.org/10.1371/journal.pone.0226329
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