AUTHOR=Arshad Muhammad , Ahmad Ashfaq , Onn Choo Wou , Sam Emmanuel Arko 

TITLE=Investigating methods for forensic analysis of social media data to support criminal investigations

JOURNAL=Frontiers in Computer Science

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1566513

DOI=10.3389/fcomp.2025.1566513

ISSN=2624-9898

ABSTRACT=Social media platforms have become a cornerstone of modern communication, and their impact on digital forensics has grown significantly. These platforms generate immense volumes of data that are invaluable for reconstructing events, identifying suspects, and corroborating evidence in criminal and civil investigations. However, forensic analysts face challenges, including privacy constraints, data integrity issues, and processing overwhelming volumes of information. This research evaluates the effectiveness of existing forensic methodologies and proposes artificial intelligence (AI) and machine learning (ML)–driven solutions to overcome these challenges. Through detailed empirical studies, including cyberbullying, fraud detection, and misinformation campaigns, the study demonstrates the effectiveness of advanced techniques such as text mining, network analysis, and metadata evaluation. These findings underscore the importance of integrating scalable technologies with ethical and legal frameworks to ensure the admissibility of social media evidence in courts of law.