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

Year: 2025
Type: article
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.
Source: Retos
DOI: 10.47197/retos.v73.116541
Language: English
Open Access status: gold
Estimated APC paid: $215
OpenAlex ID: W4414575369
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