Social Media Fake Account Detection and Prevention Using Multi-Layered AI Analysis

Devi Priya Gottumukkala; K. Mounika; S. J. Harivallika; J. Vinay Kumar; K. Surya Siddhu

doi:10.55524/ijirem.2026.13.2.8

Abstract

The exponential growth of online social networking, the proliferation of fraudulent and bot-driven accounts has emerged as a critical threat to platform integrity. These accounts are commonly exploited to disseminate false information, manipulate user behavior, and engage in various deceptive practices. Addressing this challenge requires a robust and intelligent detection mechanism capable of adapting to increasingly sophisticated evasion tactics. This paper introduces the Social Media Fake Account Detection and Prevention System (SMFADPS), a multi-layered analytical framework that assesses account authenticity through the evaluation of multiple behavioral signals. The system examines profile completeness, content credibility, follower growth irregularities, and repeated content patterns to generate intermediate suspicion scores across four specialized detection modules. An ensemble-based weighted scoring mechanism consolidates these scores into a unified risk rating, which is subsequently used to categorize accounts into distinct threat levels. The system is developed using Python, FastAPI for RESTful service delivery, and a dual-database configuration comprising PostgreSQL and MongoDB. Evaluation conducted on a large-scale dataset confirms that the multi-signal approach yields substantially higher detection accuracy and operational efficiency compared to conventional single-indicator systems.

Keywords

Social Media Security, Automated Bot Detection, Artificial Intelligence, Behavioral Signal Analysis, Anomaly Identification, Risk-Based Classification.

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Cites this article as

D. P. Gottumukkala, K. Mounika, S. J. Harivallika, J. V. Kumar, K. S. Siddhu, "Social Media Fake Account Detection and Prevention Using Multi-Layered AI Analysis", International Journal of Innovative Research in Engineering and Management (IJIREM), Vol-13, Issue-2, Page No-54-61, 2026. Available from: https://doi.org/10.55524/ijirem.2026.13.2.8