Klasifikasi dan Analisis Semantik Cyberbullying Sosial Media X: Integrasi Web Scraping dan Natural Language Processing (NLP)
DOI:
https://doi.org/10.31949/educatio.v11i2.12725Abstract
Cyberbullying di media sosial, khususnya X, telah menjadi isu kritis dengan dampak psikologis yang signifikan. Studi ini menganalisis sejauh mana cyberbullying masih terjadi di platform X dengan pendekatan semantik. Data dikumpulkan melalui proses web scraping menggunakan Selenium dengan menggunakan kategori dan kata kunci spesifik seperti “gendut” dan “bodoh” selama periode Desember 2024. Sebanyak 700 data berhasil dikumpulkan setelah melalui proses deduplikasi, yang mana memenuhi kriteria Slovin (margin of error 3.77%). Proses analisis melibatkan Natural Language Processing (NLP), termasuk text-cleaning, lowercasing, normalization, tokenization, stopword removal, klasifikasi model menggunakan model BERT yang telah di-fine-tune untuk memastikan program mengenali sebuah komentar termasuk cyberbullying atau tidak, serta pemetaan kata kunci ke 8 kategori, seperti “rasisme” dan “sara”. Hasil menunjukkan bahwa sebanyak 55,4% mengandung indikasi cyberbullying, dengan kategori seksual sebagai yang paling dominan dengan 26,6%, serta kata kunci anjing yang disebut 99 kali. Kata-kata negatif tertentu menunjukkan pola temporal yang fluktuatif, di mana intensitas cyberbullying mencapai puncak pada Minggu 4 dengan persentase tertinggi (79,1%). Temuan ini mengonfirmasi bahwa cyberbullying masih menjadi fenomena signifikan di platform X, oleh karena itu diperlukan kebijakan moderasi konten yang lebih ketat serta pengembangan sistem deteksi otomatis berbasis machine learning untuk mitigasi cyberbullying secara lebih efektif.
Keywords:
Cyberbullying, Analisis Semantik, Web Scraping, NLP, Sosial Media XDownloads
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