Enhancing Social Media Data Collection for Digital Forensic Investigations: A Web Parser Approach

Retrieving data from social media platforms and user profiles holds immense value for digital forensic investigations. However, existing tools lack efficiency in gathering evidence from online social media platforms. This paper introduces a social media web parser to extract essential user information from prominent web applications such as Facebook, Instagram, TikTok, and X. The parser gathers key artifacts, including post captions, hashtags, likes, direct links and post timestamps, offering a comprehensive and automated solution for social media data collection. This paper also studies the design, implementation, and evaluation of the parser's efficacy in extracting relevant user data across diverse platforms. The results demonstrate the parser's capability to streamline the process of information retrieval by providing a 92.12% time savings compared with manual approaches.