An Intelligent Machine Learning Framework for Fake Account Detection in Social Media Platform
Fake Account Detection, Social Media Platforms, Machine Learning, Artificial Intelligence, OCR, Social Media Security, Twitter API
The increasing use of social media platforms has led to a rise in fake accounts that spread misinformation, conduct fraudulent activities, and reduce user trust. Identifying such accounts manually is challenging due to the large volume of users and continuously evolving behavior patterns. To address this issue, this paper presents an intelligent machine learning framework for fake account detection in social media platforms.
The proposed system analyzes user profile characteristics, activity behavior, and textual information to distinguish between genuine and fake accounts. Social media APIs are used to collect account-related data, while Optical Character Recognition (OCR) extracts text from profile or post screenshots to support content analysis. Supervised machine learning models are applied to classify accounts and generate confidence scores. The framework is implemented as a web-based application, enabling efficient and scalable fake account detection to improve social media security.
Registration ID: IJVRA_701752 Published ID: IJVRA2603338
"An Intelligent Machine Learning Framework for Fake Account Detection in Social Media Platform", IJVRA - International Journal of Versatile Research and Analysis (www.IJVRA.org), ISSN:2984-8903, Vol.4, Issue 3, page no.586-591, March-2026, Available :https://ijpub.org/ijvra/papers/IJVRA2603338.pdf
Paper Reg. ID: IJVRA_701752
Published Paper Id: IJVRA2603338
Research Area: Other area not in list
Country: Coimbatore, Tamil nadu, India
ISSN: 2984-8903 | IMPACT FACTOR: 9.12 Calculated By Google Scholar | ESTD YEAR: 2023
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Publisher: IJVRA (IJ Publication) Janvi Wave
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