Chair of Performance Analysis and Sport Informatics, TUM Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany.
PLoS One. 2020 Dec 9;15(12):e0242728. doi: 10.1371/journal.pone.0242728. eCollection 2020.
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.
评价性研究主要关注技术本身及其对决策准确性的影响，而忽略了对利益相关者的影响。因此，本研究旨在调查最近引入的视频助理裁判（通常称为 VAR）对英超联赛球迷情绪的即时影响。我们分析了来自 129 场比赛的 643,251 条推文的内容，其中包括 94 个 VAR 事件，使用一种新的梯度提升方法变体来训练两个基于树的文本分类器：一个分类器用于识别与 VAR 相关的推文，另一个用于对推文的情绪进行评分。10 倍交叉验证的结果表明，我们的方法（仅使用了所有特征的一小部分来生长每棵树）比其他研究中使用的常见方法（朴素贝叶斯、支持向量机、随机森林和传统梯度树提升）在这两个分类问题上的表现都要好。关于 VAR 对球迷的影响，我们发现与这项技术裁判辅助相关的推文的平均情绪明显低于其他推文（-0.64 与 0.08；t = 45.5，p <.001）。此外，通过按每场比赛的时间顺序跟踪所有推文的平均情绪，我们可以显示出与事件发生前相比，事件发生后发布的推文的情绪明显下降。这种下降平均持续了 20 分钟。总之，我们的结果表明 VAR 主要会在 Twitter 上引起负面情绪的表达。这与之前基于问卷的其他技术裁判辅助研究的结果一致，也符合损失厌恶的心理学原则。
