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Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019

BACKGROUND: Twitter engagement between surgeons provides opportunities for international discussion of research and clinical practice. Understanding how surgical tweet chats work is important at a time when increasing reliance is being placed on virtual engagement because of the COVID-19 pandemic. M...

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Detalles Bibliográficos
Autores principales: Mackenzie, G, Grossman, R, Mayol, J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7799300/
https://www.ncbi.nlm.nih.gov/pubmed/33688941
http://dx.doi.org/10.1093/bjsopen/zraa019
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author Mackenzie, G
Grossman, R
Mayol, J
author_facet Mackenzie, G
Grossman, R
Mayol, J
author_sort Mackenzie, G
collection PubMed
description BACKGROUND: Twitter engagement between surgeons provides opportunities for international discussion of research and clinical practice. Understanding how surgical tweet chats work is important at a time when increasing reliance is being placed on virtual engagement because of the COVID-19 pandemic. METHODS: Individual tweets from the May 2019 #BJSConnect tweet chat were extracted using NodeXL, complemented by Twitter searches in an internet browser to identify responses that had not used the hashtag. Aggregate estimates of tweet views were obtained from a third-party social media tool (Twitonomy) and compared with official Twitter Analytics measurements. RESULTS: In total 37 Twitter accounts posted 248 tweets or replies relating to the tweet chat. A further 110 accounts disseminated the tweets via retweeting. Only 58.5 per cent of these tweets and 35 per cent of the tweeters were identified through a search for the #BJSConnect hashtag. The rest were identified by searching for replies (61), quoting tweets (20), and posts by @BJSurgery that used the hashtag but did not appear in the Twitter search (22). Studying all tweets revealed complex branching discussions that went beyond the discussed paper’s findings. Third-party estimates of potential reach of the tweet chat were greatly exaggerated. CONCLUSION: Understanding the extent of the discussion generated by the #BJSConnect tweet chat required looking beyond the hashtag to identify replies and other responses, which was time-consuming. Estimates of reach using a third-party tool were unreliable.
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spelling pubmed-77993002021-01-25 Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019 Mackenzie, G Grossman, R Mayol, J BJS Open Original Article BACKGROUND: Twitter engagement between surgeons provides opportunities for international discussion of research and clinical practice. Understanding how surgical tweet chats work is important at a time when increasing reliance is being placed on virtual engagement because of the COVID-19 pandemic. METHODS: Individual tweets from the May 2019 #BJSConnect tweet chat were extracted using NodeXL, complemented by Twitter searches in an internet browser to identify responses that had not used the hashtag. Aggregate estimates of tweet views were obtained from a third-party social media tool (Twitonomy) and compared with official Twitter Analytics measurements. RESULTS: In total 37 Twitter accounts posted 248 tweets or replies relating to the tweet chat. A further 110 accounts disseminated the tweets via retweeting. Only 58.5 per cent of these tweets and 35 per cent of the tweeters were identified through a search for the #BJSConnect hashtag. The rest were identified by searching for replies (61), quoting tweets (20), and posts by @BJSurgery that used the hashtag but did not appear in the Twitter search (22). Studying all tweets revealed complex branching discussions that went beyond the discussed paper’s findings. Third-party estimates of potential reach of the tweet chat were greatly exaggerated. CONCLUSION: Understanding the extent of the discussion generated by the #BJSConnect tweet chat required looking beyond the hashtag to identify replies and other responses, which was time-consuming. Estimates of reach using a third-party tool were unreliable. Oxford University Press 2020-12-13 /pmc/articles/PMC7799300/ /pubmed/33688941 http://dx.doi.org/10.1093/bjsopen/zraa019 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of BJS Society Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Mackenzie, G
Grossman, R
Mayol, J
Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019
title Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019
title_full Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019
title_fullStr Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019
title_full_unstemmed Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019
title_short Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019
title_sort beyond the hashtag: describing and understanding the full impact of the #bjsconnect tweet chat may 2019
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7799300/
https://www.ncbi.nlm.nih.gov/pubmed/33688941
http://dx.doi.org/10.1093/bjsopen/zraa019
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