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Tytuł:
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Video kills the sentiment-Exploring fans' reception of the video assistant referee in the English premier league using Twitter data.
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Autorzy:
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Kolbinger O; Chair of Performance Analysis and Sport Informatics, TUM Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany.
Knopp M; Chair of Performance Analysis and Sport Informatics, TUM Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany.
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Źródło:
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PloS one [PLoS One] 2020 Dec 09; Vol. 15 (12), pp. e0242728. Date of Electronic Publication: 2020 Dec 09 (Print Publication: 2020).
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: San Francisco, CA : Public Library of Science
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MeSH Terms:
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Social Media*
Video Recording*
Algorithms ; Humans ; Technology
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References:
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PLoS One. 2016 May 05;11(5):e0155036. (PMID: 27149621)
PLoS One. 2019 Feb 27;14(2):e0212489. (PMID: 30811456)
Springerplus. 2016 Sep 15;5(1):1572. (PMID: 27652145)
PLoS One. 2018 Mar 13;13(3):e0194317. (PMID: 29534112)
PLoS One. 2015 Sep 21;10(9):e0138441. (PMID: 26390434)
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Entry Date(s):
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Date Created: 20201209 Date Completed: 20210112 Latest Revision: 20210112
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Update Code:
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20240104
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PubMed Central ID:
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PMC7725346
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DOI:
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10.1371/journal.pone.0242728
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PMID:
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33296406
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Evaluative research of technological officiating aids in sports predominantly focuses on the respective technology and the impact on decision accuracy, whereas the impact on stakeholders is neglected. Therefore, the aim of this study was to investigate the immediate impact of the recently introduced Video Assistant Referee, often referred to as VAR, on the sentiment of fans of the English Premier League. We analyzed the content of 643,251 tweets from 129 games, including 94 VAR incidents, using a new variation of a gradient boosting approach to train two tree-based classifiers for text corpora: one classifier to identify tweets related to the VAR and another one to rate a tweet's sentiment. The results of 10-fold cross-validations showed that our approach, for which we only took a small share of all features to grow each tree, performed better than common approaches (naïve Bayes, support vector machines, random forest and traditional gradient tree boosting) used by other studies for both classification problems. Regarding the impact of the VAR on fans, we found that the average sentiment of tweets related to this technological officiating aid was significantly lower compared to other tweets (-0.64 vs. 0.08; t = 45.5, p < .001). Further, by tracking the mean sentiment of all tweets chronologically for each game, we could display that there is a significant drop of sentiment for tweets posted in the periods after an incident compared to the periods before. A plunge that persisted for 20 minutes on average. Summed up, our results provide evidence that the VAR effects predominantly expressions of negative sentiment on Twitter. This is in line with the results found in previous, questionnaire-based, studies for other technological officiating aids and also consistent with the psychological principle of loss aversion.
Competing Interests: The authors have declared that no competing interests exist.
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