Opinion and Sentiment Analysis of Palliative Care in the Era of COVID-19

During the COVID-19 pandemic, the value of palliative care has become more evident than ever. The current study quantitatively investigated the perceptions of palliative care emerging from the pandemic experience by analyzing a total of 26,494 English Tweets collected between 1 January 2020 and 1 Ja...

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Veröffentlicht in:Healthcare (Basel) 2023-03, Vol.11 (6), p.855
Hauptverfasser: Inoue, Megumi, Li, Meng-Hao, Hashemi, Mahdi, Yu, Yang, Jonnalagadda, Jahnavi, Kulkarni, Rajendra, Kestenbaum, Matthew, Mohess, Denise, Koizumi, Naoru
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container_issue 6
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container_title Healthcare (Basel)
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creator Inoue, Megumi
Li, Meng-Hao
Hashemi, Mahdi
Yu, Yang
Jonnalagadda, Jahnavi
Kulkarni, Rajendra
Kestenbaum, Matthew
Mohess, Denise
Koizumi, Naoru
description During the COVID-19 pandemic, the value of palliative care has become more evident than ever. The current study quantitatively investigated the perceptions of palliative care emerging from the pandemic experience by analyzing a total of 26,494 English Tweets collected between 1 January 2020 and 1 January 2022. Such an investigation was considered invaluable in the era of more people sharing and seeking healthcare information on social media, as well as the emerging roles of palliative care. Using a web scraping method, we reviewed 6000 randomly selected Tweets and identified four themes in the extracted Tweets: (1) Negative Impact of the Pandemic on Palliative Care; (2) Positive Impact of the Pandemic on Palliative Care; (3) Recognized Benefits of Palliative Care; (4) Myth of Palliative Care. Although a large volume of Tweets focused on the negative impact of COVID-19 on palliative care as expected, we found almost the same volume of Tweets that were focused on the positive impact of COVID-19 on palliative care. We also found a smaller volume of Tweets associated with myths about palliative care. Using these manually classified Tweets, we trained machine learning (ML) algorithms to automatically classify the remaining tweets. The automatic classification of Tweets was found to be effective in classifying the negative impact of the COVID-19.
doi_str_mv 10.3390/healthcare11060855
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We also found a smaller volume of Tweets associated with myths about palliative care. Using these manually classified Tweets, we trained machine learning (ML) algorithms to automatically classify the remaining tweets. The automatic classification of Tweets was found to be effective in classifying the negative impact of the COVID-19.</description><identifier>ISSN: 2227-9032</identifier><identifier>EISSN: 2227-9032</identifier><identifier>DOI: 10.3390/healthcare11060855</identifier><identifier>PMID: 36981512</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Analysis ; COVID-19 ; Epidemics ; Influence ; Online social networks ; Palliative care ; Palliative treatment ; Pandemics ; Public opinion ; Social networks ; United States</subject><ispartof>Healthcare (Basel), 2023-03, Vol.11 (6), p.855</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. 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source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; PubMed Central Open Access
subjects Analysis
COVID-19
Epidemics
Influence
Online social networks
Palliative care
Palliative treatment
Pandemics
Public opinion
Social networks
United States
title Opinion and Sentiment Analysis of Palliative Care in the Era of COVID-19
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