Digital Forensic Evidence Analysis In Revealing Defamation On Social Media (Twitter) Using The Static Forensics Method

Abstract

This research addresses the persistent challenge of defamation, notably prevalent on the Twitter platform, where the discovery of digital evidence is hampered by robust privacy protections. The study aims to investigate and identify digital evidence in defamation cases on Twitter, focusing on optimizing the evidence discovery process. Employing static forensics to prevent data alterations during acquisition from devices associated with defamation, the research successfully uncovered various digital evidence, including text from deleted comments, usernames, emails, and deleted image files linked to defamation. Out of the initial 28 reported data instances, 22 pieces of evidence were identified, resulting in an impressive 79% accuracy rate. The investigative procedures align with the chain of custody, ensuring the reliability of the collected evidence. This study not only contributes valuable insights into digital evidence discovery in online defamation cases but also highlights the efficacy of static forensics as a method. These findings provide a foundation for robust digital forensic practices, crucial for addressing challenges posed by online defamation on social media platforms.