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)

Israel Villarrasa-Sapiña; Frank Espinosa Cabezas; Gonzalo Monfort-Torres

doi:10.47197/retos.v53.102423

Autores/as

Israel Villarrasa-Sapiña Departamen d'educación física y esportiva, Universitat de València https://orcid.org/0000-0002-2831-1033
Frank Espinosa Cabezas Departamento de Educación Física y Deportiva https://orcid.org/0009-0004-7703-1312
Gonzalo Monfort-Torres Education Unit. Florida Universitaria, Valencia (Spain) https://orcid.org/0000-0001-8275-2238

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

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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)

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