Deteksi Cyberbullying pada Pemain Sepak Bola di Platform Media Sosial “X” Menggunakan Metode Long Short-Term Memory (LSTM)
DOI:
https://doi.org/10.62951/repeater.v3i1.382Keywords:
Cyberbulliying Detecttion, Football Player, Social Media, Long Short-Term Memory, LSTMAbstract
Social media has become a crucial part of modern life around the globe, providing users with various conveniences. However, its widespread use has also brought about new challenges, one of which is cyberbullying. This harmful issue can have serious emotional and physical effects on those targeted. Cyberbullying occurs in many areas, including sports, and soccer—a sport loved by millions—is no exception. Soccer players often face severe criticism, hate speech, and harassment on social media platforms. To tackle this problem, this study aims to create a strong model for detecting cyberbullying on the social media platform “X” using the Long Short-Term Memory (LSTM) method. By utilizing advanced machine learning techniques, the proposed model intends to identify and reduce instances of cyberbullying, helping to create a safer online space for athletes and the wider community.
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