ORIGINAL RESEARCH article
Front. Comput. Sci.
Sec. Computer Security
Volume 7 - 2025 | doi: 10.3389/fcomp.2025.1566513
Investigating Methods for Forensic Analysis of Social Media Data to Support Criminal Investigations
Provisionally accepted
- 1Technological University Dublin, Dublin, Ireland
- 2Lahore Garrison University, Lahore, Punjab, Pakistan
- 3INTI International University, Nilai, Negeri Sembilan Darul Khusus, Malaysia
- 4UNICAF, Larnaca, Larnaca, Cyprus
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
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.
Keywords: AI in forensics, cybercrime investigation, Food security, forensic analysis, Gender injustices, Social media forensics
Received: 25 Jan 2025; Accepted: 12 May 2025.
Copyright: © 2025 Arshad, Ahmad, ONN and Sam. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Muhammad Arshad, Technological University Dublin, Dublin, Ireland
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.