ABSTRACT:Social media platforms have become important sources of digital information in cybercrime investigations. Instagram contains multiple forms of potentially relevant information, including public profile information, posts, captions, comments, hashtags, images, videos, and interaction patterns. The volume and diversity of this information make purely manual examination time-consuming and difficult to scale. This paper proposes an artificial-intelligence-assisted framework for Instagram social media forensics that combines digital forensic principles with natural language processing, computer vision, and network analysis. The framework is designed to support evidence identification, classification, correlation, and prioritization while keeping a human investigator responsible for final interpretation. The methodology emphasizes lawful acquisition, preservation, hashing, documentation, and chain of custody. AI is treated as an analytical aid rather than an autonomous system for deciding whether a crime has occurred. The paper also discusses privacy, false positives, model bias, platform restrictions, and the Indian legal context for electronic records.
KEYWORDS:Social Media Forensics, Instagram, Artificial Intelligence, Cybercrime, Digital Evidence, Machine Learning, NLP, Computer Vision, Network Analysis.
SOCIAL MEDIA FORENSICS USING ARTIFICIAL INTELLIGENCE FOR CYBERCRIME INVESTIGATION: AN AI-ASSISTED FRAMEWORK FOR INSTAGRAM
RAHUL BAGWE