Exploring Baseball Spectators’ Perceptions of Robot Umpires Through Social Community Text Analysis

다국어 초록 (Multilingual Abstract)

According to Plunkett Research (2018), the global sports industry’s estimated size is 1.3trillion. Sports attract significant attention from spectators, so sports officials hold a crucial responsibility of accurately and fairly overseeing high-level sports competitions (Mascarenhas, Collins, & Mortimer, 2005). However, it’s common to witness mistakes made by umpires during games. For instance, when examining data from baseball games in the 2018 season, an average of 14 incorrect calls were made by human umpires per game (Hille, 2019). In the realm of baseball, there are ongoing trials of robot umpires in lower leagues with the aim of replacing human umpires who make incorrect judgments in strike/ball decision. In 2019, the Atlantic League in the United States became the pioneer to implement the usage of robot umpires by implementing a trackman system to determine strike/ball decisions. Major League Baseball (MLB) is also contemplating the adoption of robot umpires in the near future. However, while robot umpires are in the near future for baseball, there is a lack of research regarding the opinions of spectators on this matter. Therefore, this research would explore the sentiments and perspectives of baseball spectators concerning the introduction of robot umpires. Past research on how baseball spectators perceptions of baseball robot umpires has been survey-based one, focusing on aspects like trust in umpires, enjoyments and the behavioral outcomes (Wonseok, J., Woo,K. Y.,& Yeonheung, K., 2021). The objective of this study is to undertake a comprehensive analysis of social data through posts and comments made by real baseball spectators about their opinions on robot umpires. Social media platforms, which include online baseball communities, have gained popularity as valuable resources to exchange social support with others (Cutrona&Suhr, 1994; Fox&Duggan, 2013; Gray, Fitch, Davis, & Phillips, 1997). People who share common interests can utilize social networking sites to engage with other social media users to learn the practices easily and quickly without geographical constraints (Gilbert, 2016; Wang et al., 2021). Baseball spectators also share their opinions on robot umpires with others within social online communities. Therefore, this research aims to explore the following research question: What are the primary topics of discussion regarding robot umpires in baseball expressed on the social communities? While robot umpires have not yet been introduced in Major League Baseball games, they are currently undergoing pilot phases in lower leagues, providing baseball spectators with a glimpse of what the future implementation might hold. Spectators’ perception of robot umpires could evolve as spectators witness their use in these lower leagues and as they anticipate their introduction to the higher leagues. In other words, their expectations of robot umpires may shift, leading to the emergence of new opinions, and online community’s response might also vary over time. Therefore, this research suggests the following research questions: How does the baseball community’s reaction to robot umpires change over time? This research would derive social community data from Reddit (http://www.reddit.com), a widely used platform for social networking and online discussion. In 2015, Reddit users actively engaged in more than 88,000 subreddits (i.e., topically specialized sub-communities) and generated 83 billion-page views (Reddit, 2015). Among these subreddit, this research would crawl content data related to robot umpires from two baseball-related subreddits (r/baseball and r./MLB). This study would gather data including the post or comment, title. author’s identification, timestamp. These relevant data would be collected from 2018, before the implementation of robot umpires in the Atlantic League, up to 2023. Social analytics, encompassing text-mining and sentiment analysis, would be used to analyze social big data derived from social media content about the public’s perception of robot umpires. This research would extract useful keywords and analyze their frequency based on natural language processing and morphological analysis techniques. Additionally, through sentiment analysis, this research aims to identify public opinions expressed in the documents categorizing them as positive or negative emotions. Furthermore, this research would track the changes in the frequency of positive and negative keywords related to robot umpires. This study anticipates that keyword analysis through text mining would suggest words associated with expectations and concerns regarding the implementation of robot umpires, frustration with human umpire errors, and calls for faster adoption. Furthermore, this research predict that spectator’s perception of robot umpires would be predominantly positive, with positive sentiment outweighing negative ones. Nevertheless, following the introduction of robot umpires in the lower leagues, this research expects that there would be some increase in negative sentiment due to apprehensions and concerns about the technical aspects. By this research, the result could significantly influence the adoption of robot umpires in big leagues such as MLB. By delving into the perceptions of baseball fans, this research would contribute to provide valuable insights that have the potential to impact the decision-making process for those considering the replacement of human umpires with robot umpires. Moreover, this study would contribute to the understanding of how the introduction of innovative technologies in sports affect emotions within the social communities.