Árbitro asistente de vídeo en Twitter: un análisis del sentimiento de los fans basado en la minería de textos (Video assistant referee on Twitter: a text-mining-based analysis of fan sentiment)

Autores/as

DOI:

https://doi.org/10.47197/retos.v53.102423

Palabras clave:

VAR, football, fútbol, fans, twitter, análisis de datos

Resumen

El objetivo de la investigación era conocer la opinión de los usuarios de Twitter sobre el Video Assistant Referee, conocido por el acrónimo VAR, durante su implantación en la Premier League, a través de las palabras, emojis y temas más relacionados con los términos de búsqueda. Mediante un algoritmo, se realizó una búsqueda sistemática de una serie de palabras utilizadas en la red social Twitter. El resultado de esta búsqueda se procesó con la intención de obtener resultados cuantitativos en términos de frecuencia de palabras buscadas, términos y emojis que las acompañan, así como temas emergentes. Los resultados mostraron que, entre los bigramas, "premier league" era el más repetido. Entre los trigramas, la asociación entre las palabras "var ruin football" y "var kill football". Los principales temas encontrados contenían las palabras "ruin", "football", "fuck" y "kill". De los emojis más utilizados, sólo dos tenían connotaciones positivas. En conclusión, se observó una tendencia de opinión negativa sobre el VAR.

Palabras clave: var, football, fútbol, fans, Twitter, análisis de datos.

Abstract. The objective of the research was to know the opinion of Twitter users about the Video Assistant Referee, known by the acronym VAR, during its implantation in the Premier League, through the words, emojis and topics most related to the search terms. Using an algorithm, a systematic search was carried out during a given period of time for a series of words used in the Twitter social network. The result of this search was processed to obtain quantitative results in terms of the frequency of the searched words, terms and emojis that accompanied them as well as emerging themes. The results showed that among the bigrams, "premier league" was the most repeated. Among the trigrams, the association between the words "var ruin football" and "var kill football" stands out. The main themes found contained the words "ruin", "football", "fuck" and "kill". Of the most used emojis, only two had positive connotations. In conclusion, a trend of negative opinions about VAR was observed.

Keywords: var, football, soccer, fans, Twitter, data analysis.

Citas

Alharbi, A. S. M., & de Doncker, E. (2019). Twitter sentiment analysis with a deep neural network: An enhanced approach using user behavioral information. Cognitive Systems Research, 54, 50-61. https://doi.org/10.1016/j.cogsys.2018.10.001

Aza Conejo, R., Banos-Pino, J., Canal Dominguez, J. F., & Rodriguez Guerrero, P. (2007). The economic impact of football on the regional economy. International Journal of Sport Management and Marketing, 2(5-6), 459-474. https://doi.org/10.1504/IJSMM.2007.013961

Barajas, A., & Urrutia, I. (2007). Economic impact of support in Spanish professional football. International Journal of Sports Marketing and Sponsorship, 8(3), 67-74. https://doi.org/10.1108/IJSMS-08-03-2007-B007

Blei, D., Ng, A., & Jordan, M. (2001). Latent Dirichlet Allocation. Advances in Neural Information Processing Systems, 14. MIT Press. Recuperado de https://proceedings.neurips.cc/paper/2001/hash/296472c9542ad4d4788d543508116cbc-Abstract.html

Blok, A., & Pedersen, M. A. (2014). Complementary social science? Quali-quantitative experiments in a Big Data world. Big Data & Society, 1(2), 2053951714543908. https://doi.org/10.1177/2053951714543908

Borodin, A., Roberts, G. O., Rosenthal, J. S., & Tsaparas, P. (2005). Link analysis ranking: Algorithms, theory, and experiments. ACM Transactions on Internet Technology, 5(1), 231-297. https://doi.org/10.1145/1052934.1052942

Brymer, R., Rodenberg, R. M., Zheng, H., & Holcomb, T. R. (2021). College Football Referee Bias and Sports Bet-ting Impact. Eastern Economic Journal, 47(1), 91-106. https://doi.org/10.1057/s41302-020-00180-6

Büschken, J., & Allenby, G. M. (2016). Sentence-Based Text Analysis for Customer Reviews. Marketing Science, 35(6), 953-975. https://doi.org/10.1287/mksc.2016.0993

Carbonell, J. P. Z. (2013). Medios de comunicación, globalización y futbol. Imaginarios y discursos en la mundializa-ción de la rivalidad entre el Barcelona y el Real Madrid. Revista Impetus, 7(1), 73-78.

Chadwick, S., & Arthur, D. (2008). International Cases in the Business of Sport. Routledge.

Coombs, D. S., & Osborne, A. C. (2022). Routledge Handbook of Sport Fans and Fandom. Routledge.

Coteron Lopez, F. J., & Bello Garrido, M. F. (2012). Barça-Madrid: Una rivalidad global. Análisis del derbi a través de la prensa escrita española. Estudios Sobre el Mensaje Periodistico, 18(2), 459-474.

Dawley, L. (2009). Social network knowledge construction: Emerging virtual world pedagogy. On the Horizon, 17(2), 109-121. https://doi.org/10.1108/10748120910965494

Eagleman, A. N. (2013). Acceptance, motivations, and usage of social media as a marketing communications tool amongst employees of sport national governing bodies. Sport Management Review, 16(4), 488-497. https://doi.org/10.1016/j.smr.2013.03.004

Fédération Internationale de Football Association. (2019). Laws of the game: Video Assistant Referee (VAR) protocol. Fédération Internationale de Football Association.

Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport Management Review, 18(2), 166-181. https://doi.org/10.1016/j.smr.2014.11.001

Fişne, M., Bardakçi, S., & Hasaan, A. (2021). Analysis of Perceptions of Turkish Fans of Video-Assistant-Referees in Elite Soccer. South African Journal for Research in Sport, Physical Education and Recreation, 43(2), 29-46. https://doi.org/10.10520/ejc-sport_v43_n2_a3

Garland, J., Malcolm, D., & Rowe, M. (2013). The Future of Football: Challenges for the Twenty-first Century. Routledge. https://doi.org/10.4324/9781315039800

Hamsund, T., & Scelles, N. (2021). Fans’ Perceptions towards Video Assistant Referee (VAR) in the English Premier League. Journal of Risk and Financial Management, 14(12), 573. https://doi.org/10.3390/jrfm14120573

Jianqiang, Z., & Xiaolin, G. (2017). Comparison Research on Text Pre-processing Methods on Twitter Sentiment Analysis. IEEE Access, 5, 2870-2879. https://doi.org/10.1109/ACCESS.2017.2672677

Kearney, M. W. (2019). rtweet: Collecting and analyzing Twitter data. Journal of Open Source Software, 4(42), 1829. https://doi.org/10.21105/joss.01829

Larkin, P., Berry, J., Dawson, B., & Lay, B. (2011). Perceptual and decision-making skills of Australian football um-pires. International Journal of Performance Analysis in Sport, 11(3), 427-437. https://doi.org/10.1080/24748668.2011.11868562

Marres, N., & Weltevrede, E. (2013). Scraping the Social? Journal of Cultural Economy, 6(3), 313-335. https://doi.org/10.1080/17530350.2013.772070

Mascarenhas, D. R. D., Collins, D., & Mortimer, P. (2005). Elite Refereeing Performance: Developing a Model for Sport Science Support. The Sport Psychologist, 19(4), 364-379. https://doi.org/10.1123/tsp.19.4.364

Mayring, P. (2015). Qualitative Content Analysis: Theoretical Background and Procedures. En A. Bikner-Ahsbahs, C. Knipping, & N. Presmeg (Eds.), Approaches to Qualitative Research in Mathematics Education: Examples of Methodology and Methods (pp. 365-380). Dordrecht: Springer Netherlands. https://doi.org/10.1007/978-94-017-9181-6_13

Qaiser, S., & Ali, R. (2018). Text Mining: Use of TF-IDF to Examine the Relevance of Words to Documents. Interna-tional Journal of Computer Applications, 181(1), 0975-8887. https://doi.org/10.5120/ijca2018917395.

Sanchez, M., & Garcia, A. L. (2019). The Interaction between Audio and the Video Assistant Referee in Football. En The Use of Video Technologies in Refereeing Football and Other Sports (1st Edition). New York: Routledge.

Scanlon, C., Griggs, G., & McGillick, C. (2022). ‘It’s not football anymore’: Perceptions of the video assistant referee by english premier league football fans. Soccer & Society, 0(0), 1-13. https://doi.org/10.1080/14660970.2022.2033731

Stoney, E., & Fletcher, T. (2021). “Are Fans in the Stands an Afterthought?”: Sports Events, Decision-Aid Technolo-gies, and the Television Match Official in Rugby Union. Communication & Sport, 9(6), 1008-1029. https://doi.org/10.1177/2167479520903405

Sutter, M., & Kocher, M. G. (2004). Favoritism of agents – The case of referees’ home bias. Journal of Economic Psy-chology, 25(4), 461-469. https://doi.org/10.1016/S0167-4870(03)00013-8

Takhteyev, Y., Gruzd, A., & Wellman, B. (2012). Geography of Twitter networks. Social Networks, 34(1), 73-81. https://doi.org/10.1016/j.socnet.2011.05.006

Tinati, R., Halford, S., Carr, L., & Pope, C. (2014). Big Data: Methodological Challenges and Approaches for Socio-logical Analysis. Sociology, 48(4), 663-681. https://doi.org/10.1177/0038038513511561

Tingle, J., & Armenteros, M. (2019). Instant Replay in the National Football League. En The Use of Video Technologies in Refereeing Football and Other Sports (1st Edition). New York: Routledge.

van Dijck, J., & Poell, T. (2013, agosto 12). Understanding Social Media Logic [SSRN Scholarly Paper]. Rochester, NY. Recuperado de https://papers.ssrn.com/abstract=2309065

Williams, M., Burnap, P., & Sloan, L. (2017). Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users’ Views, Online Context and Algorithmic Estimation. Sociology, 0, 1-20.

Winand, M., Schneiders, C., Merten, S., & Marlier, M. (2021). Sports fans and innovation: An analysis of football fans’ satisfaction with video assistant refereeing through social identity and argumentative theories. Journal of Business Research, 136, 99-109. https://doi.org/10.1016/j.jbusres.2021.07.029

Wunderlich, F., & Memmert, D. (2022). A big data analysis of Twitter data during premier league matches: Do tweets contain information valuable for in-play forecasting of goals in football? Social Network Analysis and Mining, 12(1). Scopus. https://doi.org/10.1007/s13278-021-00842-z

Yao, Q., Li, R. Y. M., Song, L., & Crabbe, M. J. C. (2021). Construction safety knowledge sharing on Twitter: A so-cial network analysis. Safety Science, 143, 105411. https://doi.org/10.1016/j.ssci.2021.105411

Descargas

Publicado

2024-04-01

Cómo citar

Villarrasa-Sapiña, I., Espinosa Cabezas, F., & Monfort-Torres, G. (2024). Árbitro asistente de vídeo en Twitter: un análisis del sentimiento de los fans basado en la minería de textos (Video assistant referee on Twitter: a text-mining-based analysis of fan sentiment). Retos, 53, 91–99. https://doi.org/10.47197/retos.v53.102423

Número

Sección

Artículos de carácter científico: trabajos de investigaciones básicas y/o aplicadas

Artículos más leídos del mismo autor/a