Analisis Penyebaran Informasi Hoaks pada Media Sosial di Era Digital Menggunakan Metode Systematic Literature Review

Abstract

The rapid development of social media has significantly changed how information is created, shared, and consumed by society. Alongside these advancements, the spread of misinformation and hoaxes has become a major challenge, affecting public trust, social stability, and decision-making. Hoaxes are intentionally fabricated or misleading information disseminated through digital platforms to manipulate public opinion or create confusion. This study aims to analyze the dissemination of hoax information on social media and identify effective prevention strategies through a Systematic Literature Review (SLR). Relevant scientific articles published between 2021 and 2025 were collected from reputable databases using predefined inclusion and exclusion criteria. The findings indicate that Facebook, WhatsApp, X (formerly Twitter), Instagram, and TikTok are the primary platforms for hoax dissemination. Factors influencing the rapid spread of hoaxes include low digital literacy, algorithm-driven content distribution, emotional user responses, and the ease of sharing information. Furthermore, machine learning, deep learning, and Natural Language Processing (NLP) have become the dominant approaches for automated hoax detection. Preventive efforts require collaboration among governments, digital platforms, educational institutions, and society through digital literacy programs, content verification mechanisms, and advanced detection technologies. This study provides a comprehensive overview of current research trends and offers recommendations for improving information integrity in digital environments.