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Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data

Physicians’ beliefs and attitudes about COVID-19 are important to ascertain because of their central role in providing care to patients during the pandemic. Identifying topics and sentiments discussed by physicians and other healthcare workers can lead to identification of gaps relating to the COVID...

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Detalles Bibliográficos
Autores principales: Sullivan, Katherine J., Burden, Marisha, Keniston, Angela, Banda, Juan M., Hunter, Lawrence E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958992/
https://www.ncbi.nlm.nih.gov/pubmed/33691008
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author Sullivan, Katherine J.
Burden, Marisha
Keniston, Angela
Banda, Juan M.
Hunter, Lawrence E.
author_facet Sullivan, Katherine J.
Burden, Marisha
Keniston, Angela
Banda, Juan M.
Hunter, Lawrence E.
author_sort Sullivan, Katherine J.
collection PubMed
description Physicians’ beliefs and attitudes about COVID-19 are important to ascertain because of their central role in providing care to patients during the pandemic. Identifying topics and sentiments discussed by physicians and other healthcare workers can lead to identification of gaps relating to the COVID-19 pandemic response within the healthcare system. To better understand physicians’ perspectives on the COVID-19 response, we extracted Twitter data from a specific user group that allows physicians to stay anonymous while expressing their perspectives about the COVID-19 pandemic. All tweets were in English. We measured most frequent bigrams and trigrams, compared sentiment analysis methods, and compared our findings to a larger Twitter dataset containing general COVID-19 related discourse. We found significant differences between the two datasets for specific topical phrases. No statistically significant difference was found in sentiments between the two datasets, and both trended slightly more positive than negative. Upon comparison to manual sentiment analysis, it was determined that these sentiment analysis methods should be improved to accurately capture sentiments of anonymous physician data. Anonymous physician social media data is a unique source of information that provides important insights into COVID-19 perspectives.
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spelling pubmed-79589922021-03-15 Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data Sullivan, Katherine J. Burden, Marisha Keniston, Angela Banda, Juan M. Hunter, Lawrence E. Pac Symp Biocomput Article Physicians’ beliefs and attitudes about COVID-19 are important to ascertain because of their central role in providing care to patients during the pandemic. Identifying topics and sentiments discussed by physicians and other healthcare workers can lead to identification of gaps relating to the COVID-19 pandemic response within the healthcare system. To better understand physicians’ perspectives on the COVID-19 response, we extracted Twitter data from a specific user group that allows physicians to stay anonymous while expressing their perspectives about the COVID-19 pandemic. All tweets were in English. We measured most frequent bigrams and trigrams, compared sentiment analysis methods, and compared our findings to a larger Twitter dataset containing general COVID-19 related discourse. We found significant differences between the two datasets for specific topical phrases. No statistically significant difference was found in sentiments between the two datasets, and both trended slightly more positive than negative. Upon comparison to manual sentiment analysis, it was determined that these sentiment analysis methods should be improved to accurately capture sentiments of anonymous physician data. Anonymous physician social media data is a unique source of information that provides important insights into COVID-19 perspectives. 2021 /pmc/articles/PMC7958992/ /pubmed/33691008 Text en http://creativecommons.org/licenses/by-nc/4.0/ Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC) 4.0 License.
spellingShingle Article
Sullivan, Katherine J.
Burden, Marisha
Keniston, Angela
Banda, Juan M.
Hunter, Lawrence E.
Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data
title Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data
title_full Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data
title_fullStr Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data
title_full_unstemmed Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data
title_short Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data
title_sort characterization of anonymous physician perspectives on covid-19 using social media data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958992/
https://www.ncbi.nlm.nih.gov/pubmed/33691008
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