Exploring Baseball Spectators’ Perceptions of Robot Umpires Through Social Community Text Analysis
저자
발행기관
학술지명
권호사항
발행연도
2023
작성언어
English
주제어
KDC
325
자료형태
학술저널
발행기관 URL
수록면
311-312(2쪽)
제공처
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.
더보기분석정보
서지정보 내보내기(Export)
닫기소장기관 정보
닫기권호소장정보
닫기오류접수
닫기오류 접수 확인
닫기음성서비스 신청
닫기음성서비스 신청 확인
닫기이용약관
닫기학술연구정보서비스 이용약관 (2017년 1월 1일 ~ 현재 적용)
학술연구정보서비스(이하 RISS)는 정보주체의 자유와 권리 보호를 위해 「개인정보 보호법」 및 관계 법령이 정한 바를 준수하여, 적법하게 개인정보를 처리하고 안전하게 관리하고 있습니다. 이에 「개인정보 보호법」 제30조에 따라 정보주체에게 개인정보 처리에 관한 절차 및 기준을 안내하고, 이와 관련한 고충을 신속하고 원활하게 처리할 수 있도록 하기 위하여 다음과 같이 개인정보 처리방침을 수립·공개합니다.
주요 개인정보 처리 표시(라벨링)
목 차
3년
또는 회원탈퇴시까지5년
(「전자상거래 등에서의 소비자보호에 관한3년
(「전자상거래 등에서의 소비자보호에 관한2년
이상(개인정보보호위원회 : 개인정보의 안전성 확보조치 기준)개인정보파일의 명칭 | 운영근거 / 처리목적 | 개인정보파일에 기록되는 개인정보의 항목 | 보유기간 | |
---|---|---|---|---|
학술연구정보서비스 이용자 가입정보 파일 | 한국교육학술정보원법 | 필수 | ID, 비밀번호, 성명, 생년월일, 신분(직업구분), 이메일, 소속분야, 웹진메일 수신동의 여부 | 3년 또는 탈퇴시 |
선택 | 소속기관명, 소속도서관명, 학과/부서명, 학번/직원번호, 휴대전화, 주소 |
구분 | 담당자 | 연락처 |
---|---|---|
KERIS 개인정보 보호책임자 | 정보보호본부 김태우 | - 이메일 : lsy@keris.or.kr - 전화번호 : 053-714-0439 - 팩스번호 : 053-714-0195 |
KERIS 개인정보 보호담당자 | 개인정보보호부 이상엽 | |
RISS 개인정보 보호책임자 | 대학학술본부 장금연 | - 이메일 : giltizen@keris.or.kr - 전화번호 : 053-714-0149 - 팩스번호 : 053-714-0194 |
RISS 개인정보 보호담당자 | 학술진흥부 길원진 |
자동로그아웃 안내
닫기인증오류 안내
닫기귀하께서는 휴면계정 전환 후 1년동안 회원정보 수집 및 이용에 대한
재동의를 하지 않으신 관계로 개인정보가 삭제되었습니다.
(참조 : RISS 이용약관 및 개인정보처리방침)
신규회원으로 가입하여 이용 부탁 드리며, 추가 문의는 고객센터로 연락 바랍니다.
- 기존 아이디 재사용 불가
휴면계정 안내
RISS는 [표준개인정보 보호지침]에 따라 2년을 주기로 개인정보 수집·이용에 관하여 (재)동의를 받고 있으며, (재)동의를 하지 않을 경우, 휴면계정으로 전환됩니다.
(※ 휴면계정은 원문이용 및 복사/대출 서비스를 이용할 수 없습니다.)
휴면계정으로 전환된 후 1년간 회원정보 수집·이용에 대한 재동의를 하지 않을 경우, RISS에서 자동탈퇴 및 개인정보가 삭제처리 됩니다.
고객센터 1599-3122
ARS번호+1번(회원가입 및 정보수정)