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Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?

BACKGROUND: Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed us...

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Autores principales: Mondal, Himel, Parvanov, Emil D., Singla, Rajeev K., Rayan, Rehab A., Nawaz, Faisal A., Ritschl, Valentin, Eibensteiner, Fabian, Siva Sai, Chandragiri, Cenanovic, Merisa, Devkota, Hari Prasad, Hribersek, Mojca, De, Ronita, Klager, Elisabeth, Kletecka-Pulker, Maria, Völkl-Kernstock, Sabine, Khalid, Garba M., Lordan, Ronan, Găman, Mihnea-Alexandru, Shen, Bairong, Stamm, Tanja, Willschke, Harald, Atanasov, Atanas G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523003/
https://www.ncbi.nlm.nih.gov/pubmed/36186802
http://dx.doi.org/10.3389/fmed.2022.961360
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author Mondal, Himel
Parvanov, Emil D.
Singla, Rajeev K.
Rayan, Rehab A.
Nawaz, Faisal A.
Ritschl, Valentin
Eibensteiner, Fabian
Siva Sai, Chandragiri
Cenanovic, Merisa
Devkota, Hari Prasad
Hribersek, Mojca
De, Ronita
Klager, Elisabeth
Kletecka-Pulker, Maria
Völkl-Kernstock, Sabine
Khalid, Garba M.
Lordan, Ronan
Găman, Mihnea-Alexandru
Shen, Bairong
Stamm, Tanja
Willschke, Harald
Atanasov, Atanas G.
author_facet Mondal, Himel
Parvanov, Emil D.
Singla, Rajeev K.
Rayan, Rehab A.
Nawaz, Faisal A.
Ritschl, Valentin
Eibensteiner, Fabian
Siva Sai, Chandragiri
Cenanovic, Merisa
Devkota, Hari Prasad
Hribersek, Mojca
De, Ronita
Klager, Elisabeth
Kletecka-Pulker, Maria
Völkl-Kernstock, Sabine
Khalid, Garba M.
Lordan, Ronan
Găman, Mihnea-Alexandru
Shen, Bairong
Stamm, Tanja
Willschke, Harald
Atanasov, Atanas G.
author_sort Mondal, Himel
collection PubMed
description BACKGROUND: Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed users. The world has been challenged by the COVID-19 pandemic in the last several years. Measures to combat the pandemic continue to evolve worldwide, and ideas and opinions on optimal counteraction strategies are of high interest. OBJECTIVE: This study aimed to validate the use of Twitter as a crowdsourcing platform in order to gain an understanding of public opinion on what measures can help to end the COVID-19 pandemic faster. METHODS: This cross-sectional study was conducted during the period from December 22, 2021, to February 4, 2022. Tweets were posted by accounts operated by the authors, asking “How to faster end the COVID-19 pandemic?” and encouraging the viewers to comment on measures that they perceive would be effective to achieve this goal. The ideas from the users' comments were collected and categorized into two major themes – personal and institutional measures. In the final stage of the campaign, a Twitter poll was conducted to get additional comments and to estimate which of the two groups of measures were perceived to be important amongst Twitter users. RESULTS: The crowdsourcing campaign generated seventeen suggested measures categorized into two major themes (personal and institutional) that received a total of 1,727 endorsements (supporting comments, retweets, and likes). The poll received a total of 325 votes with 58% of votes underscoring the importance of both personal and institutional measures, 20% favoring personal measures, 11% favoring institutional measures, and 11% of the votes given just out of curiosity to see the vote results. CONCLUSIONS: Twitter was utilized successfully for crowdsourcing ideas on strategies how to end the COVID-19 pandemic faster. The results indicate that the Twitter community highly values the significance of both personal responsibility and institutional measures to counteract the pandemic. This study validates the use of Twitter as a primary tool that could be used for crowdsourcing ideas with healthcare significance.
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spelling pubmed-95230032022-10-01 Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster? Mondal, Himel Parvanov, Emil D. Singla, Rajeev K. Rayan, Rehab A. Nawaz, Faisal A. Ritschl, Valentin Eibensteiner, Fabian Siva Sai, Chandragiri Cenanovic, Merisa Devkota, Hari Prasad Hribersek, Mojca De, Ronita Klager, Elisabeth Kletecka-Pulker, Maria Völkl-Kernstock, Sabine Khalid, Garba M. Lordan, Ronan Găman, Mihnea-Alexandru Shen, Bairong Stamm, Tanja Willschke, Harald Atanasov, Atanas G. Front Med (Lausanne) Medicine BACKGROUND: Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed users. The world has been challenged by the COVID-19 pandemic in the last several years. Measures to combat the pandemic continue to evolve worldwide, and ideas and opinions on optimal counteraction strategies are of high interest. OBJECTIVE: This study aimed to validate the use of Twitter as a crowdsourcing platform in order to gain an understanding of public opinion on what measures can help to end the COVID-19 pandemic faster. METHODS: This cross-sectional study was conducted during the period from December 22, 2021, to February 4, 2022. Tweets were posted by accounts operated by the authors, asking “How to faster end the COVID-19 pandemic?” and encouraging the viewers to comment on measures that they perceive would be effective to achieve this goal. The ideas from the users' comments were collected and categorized into two major themes – personal and institutional measures. In the final stage of the campaign, a Twitter poll was conducted to get additional comments and to estimate which of the two groups of measures were perceived to be important amongst Twitter users. RESULTS: The crowdsourcing campaign generated seventeen suggested measures categorized into two major themes (personal and institutional) that received a total of 1,727 endorsements (supporting comments, retweets, and likes). The poll received a total of 325 votes with 58% of votes underscoring the importance of both personal and institutional measures, 20% favoring personal measures, 11% favoring institutional measures, and 11% of the votes given just out of curiosity to see the vote results. CONCLUSIONS: Twitter was utilized successfully for crowdsourcing ideas on strategies how to end the COVID-19 pandemic faster. The results indicate that the Twitter community highly values the significance of both personal responsibility and institutional measures to counteract the pandemic. This study validates the use of Twitter as a primary tool that could be used for crowdsourcing ideas with healthcare significance. Frontiers Media S.A. 2022-09-16 /pmc/articles/PMC9523003/ /pubmed/36186802 http://dx.doi.org/10.3389/fmed.2022.961360 Text en Copyright © 2022 Mondal, Parvanov, Singla, Rayan, Nawaz, Ritschl, Eibensteiner, Siva Sai, Cenanovic, Devkota, Hribersek, De, Klager, Kletecka-Pulker, Völkl-Kernstock, Khalid, Lordan, Găman, Shen, Stamm, Willschke and Atanasov. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Mondal, Himel
Parvanov, Emil D.
Singla, Rajeev K.
Rayan, Rehab A.
Nawaz, Faisal A.
Ritschl, Valentin
Eibensteiner, Fabian
Siva Sai, Chandragiri
Cenanovic, Merisa
Devkota, Hari Prasad
Hribersek, Mojca
De, Ronita
Klager, Elisabeth
Kletecka-Pulker, Maria
Völkl-Kernstock, Sabine
Khalid, Garba M.
Lordan, Ronan
Găman, Mihnea-Alexandru
Shen, Bairong
Stamm, Tanja
Willschke, Harald
Atanasov, Atanas G.
Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?
title Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?
title_full Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?
title_fullStr Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?
title_full_unstemmed Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?
title_short Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?
title_sort twitter-based crowdsourcing: what kind of measures can help to end the covid-19 pandemic faster?
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523003/
https://www.ncbi.nlm.nih.gov/pubmed/36186802
http://dx.doi.org/10.3389/fmed.2022.961360
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