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Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study

BACKGROUND: Reasons such as the lack of information on the COVID-19 disease, lack of proven treatment for it, uncertainty about the duration of the pandemic, or social isolation affect people’s mental health. This study aimed to analyze the emotional type and intensity in tweets on toothache posted...

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Autores principales: Altan, Halenur, Coşgun, Alem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386340/
https://www.ncbi.nlm.nih.gov/pubmed/34433449
http://dx.doi.org/10.1186/s12903-021-01778-8
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author Altan, Halenur
Coşgun, Alem
author_facet Altan, Halenur
Coşgun, Alem
author_sort Altan, Halenur
collection PubMed
description BACKGROUND: Reasons such as the lack of information on the COVID-19 disease, lack of proven treatment for it, uncertainty about the duration of the pandemic, or social isolation affect people’s mental health. This study aimed to analyze the emotional type and intensity in tweets on toothache posted during the COVID-19 pandemic. METHODS: Using the Twitter Search API, we collected tweets in English associated with the keywords “Corona, Toothache” “Corona, Tooth, Pain” “Corona, Dental Pain” “Covid-19, Toothache” “Covid-19, Tooth, Pain” and “Covid-19, Dental Pain” posted between March 11, 2020 and June 30, 2020 all around the world. After the relevant inclusion and exclusion criteria were applied, 426 posts were selected and analyzed using the CrystalFeel algorithm, a sensitivity analytical technology with proven accuracy. The chi-square test (SPSS v23, IBM) was used to compare emotions and emotional intensities according to the words used. RESULTS: It was determined that 80.3% of the participants experienced fear and 61.7% had a negative emotional intensity. There was no statistically significant difference between the distributions of emotions according to the words without time distinction (p = 0.136). There was a statistically significant difference between the distributions of emotional intensity according to the words without time distinction (p = 0.006). The keyword “Corona, Toothache” was used the most frequently by 30.8% of the participants. CONCLUSIONS: This study is the first to analyze the emotional reactions of individuals who experienced toothaches during the COVID-19 pandemic using the CrystalFeel algorithm. Monitoring the social media posts of individuals experiencing toothache during the pandemic will help reduce fear and anger emotions and design public information messages that are compatible with the target group’s needs.
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spelling pubmed-83863402021-08-25 Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study Altan, Halenur Coşgun, Alem BMC Oral Health Research BACKGROUND: Reasons such as the lack of information on the COVID-19 disease, lack of proven treatment for it, uncertainty about the duration of the pandemic, or social isolation affect people’s mental health. This study aimed to analyze the emotional type and intensity in tweets on toothache posted during the COVID-19 pandemic. METHODS: Using the Twitter Search API, we collected tweets in English associated with the keywords “Corona, Toothache” “Corona, Tooth, Pain” “Corona, Dental Pain” “Covid-19, Toothache” “Covid-19, Tooth, Pain” and “Covid-19, Dental Pain” posted between March 11, 2020 and June 30, 2020 all around the world. After the relevant inclusion and exclusion criteria were applied, 426 posts were selected and analyzed using the CrystalFeel algorithm, a sensitivity analytical technology with proven accuracy. The chi-square test (SPSS v23, IBM) was used to compare emotions and emotional intensities according to the words used. RESULTS: It was determined that 80.3% of the participants experienced fear and 61.7% had a negative emotional intensity. There was no statistically significant difference between the distributions of emotions according to the words without time distinction (p = 0.136). There was a statistically significant difference between the distributions of emotional intensity according to the words without time distinction (p = 0.006). The keyword “Corona, Toothache” was used the most frequently by 30.8% of the participants. CONCLUSIONS: This study is the first to analyze the emotional reactions of individuals who experienced toothaches during the COVID-19 pandemic using the CrystalFeel algorithm. Monitoring the social media posts of individuals experiencing toothache during the pandemic will help reduce fear and anger emotions and design public information messages that are compatible with the target group’s needs. BioMed Central 2021-08-25 /pmc/articles/PMC8386340/ /pubmed/34433449 http://dx.doi.org/10.1186/s12903-021-01778-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Altan, Halenur
Coşgun, Alem
Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study
title Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study
title_full Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study
title_fullStr Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study
title_full_unstemmed Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study
title_short Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study
title_sort analysis of tweets on toothache during the covid-19 pandemic using the crystalfeel algorithm: a cross-sectional study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386340/
https://www.ncbi.nlm.nih.gov/pubmed/34433449
http://dx.doi.org/10.1186/s12903-021-01778-8
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