Analyzing network dynamics and dominant hate speech types in Twitter conversations during professional football matches

Introduction: Persib is one of Indonesia's most popular football clubs, and it has a strong fan base. Unfortunately, this does not prevent it from being exposed to negative opinions when it competes. Objective: This study aims to describe the structural features of the networks and identify the dominant types of hate speech while Persib is in a match on Twitter. Methodology: This research employed a two-phase, mixed-method approach of a digital netnography with social network analysis and thematic content analysis of 413,688 tweets during the Liga 1 Sport Event. Results: This study's findings indicate that Persib is very vulnerable to receive hate speech from fans when they are in match. Based on the analysis, the most frequently occurring speech was insulting or cursing, blaming, threatening, satirical, and critical. Discussion: This hate speech is directed at Persib players, coaches, and management. Hate speech directed at Persib was dominated by local languages ​​or Sundanese. The topics of hate speech were primarily related to the course of the match, player performance, ticket system, management, and the broadcast of the match, which was considered lacking. Conclusions: These findings can be used to evaluate Persib management and provide a basis for developing strategies to combat hate speech on Twitter. Hate speech experienced by Persib also occurred because Persib fans believe that Persib as a football club only focuses on social media image building. Thus, Persib must consider the hate speech that befell Persib as urgent and need to be handled immediately because it can potentially threaten Persib's image.

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Publication Details

Journal
Retos
Published
2025-09-28
DOI
https://doi.org/10.47197/retos.v73.116541
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
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0.00
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article

Analyzing network dynamics and dominant hate speech types in Twitter conversations during professional football matches

Eny Ratnasari, Centurion Chandratama Priyatna, Nindi Aristi, Agus Rahmat
Retos
Hate Speech and Cyberbullying Detection
article

Analyzing network dynamics and dominant hate speech types in Twitter conversations during professional football matches

Eny Ratnasari, Centurion Chandratama Priyatna, Nindi Aristi, Agus Rahmat
article en

Abstract

Introduction: Persib is one of Indonesia's most popular football clubs, and it has a strong fan base. Unfortunately, this does not prevent it from being exposed to negative opinions when it competes. Objective: This study aims to describe the structural features of the networks and identify the dominant types of hate speech while Persib is in a match on Twitter. Methodology: This research employed a two-phase, mixed-method approach of a digital netnography with social network analysis and thematic content analysis of 413,688 tweets during the Liga 1 Sport Event. Results: This study's findings indicate that Persib is very vulnerable to receive hate speech from fans when they are in match. Based on the analysis, the most frequently occurring speech was insulting or cursing, blaming, threatening, satirical, and critical. Discussion: This hate speech is directed at Persib players, coaches, and management. Hate speech directed at Persib was dominated by local languages ​​or Sundanese. The topics of hate speech were primarily related to the course of the match, player performance, ticket system, management, and the broadcast of the match, which was considered lacking. Conclusions: These findings can be used to evaluate Persib management and provide a basis for developing strategies to combat hate speech on Twitter. Hate speech experienced by Persib also occurred because Persib fans believe that Persib as a football club only focuses on social media image building. Thus, Persib must consider the hate speech that befell Persib as urgent and need to be handled immediately because it can potentially threaten Persib's image.

RetosVol. 73
Padjadjaran University (ID)
Openalex Percentile: Top 86%
Hate Speech and Cyberbullying Detection
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Analyzing network dynamics and dominant hate speech types in Twitter conversations during professional football matches — Eny Ratnasari, Centurion Chandratama Priyatna, et al. · Retos (2025) | TGRS Research Map | TGRS