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@article{179507,
        author = {B.Nikitha and Venkatesh Sharma and B.Lakshmi Charan Reddy and K.Tarun Singh and A.Sravanthi},
        title = {Profile Hunter: A Smart Framework for Identifying Social Media Impersonation Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {8392-8396},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179507},
        abstract = {Social networks have become an integral 
part of modern life, with millions of users actively 
participating on platforms such as Facebook, Twitter, 
and 
LinkedIn. 
These 
platforms 
facilitate 
communication and connection, allowing users to 
interact 
seamlessly 
regardless 
of 
geographic 
boundaries. However, they also present significant 
challenges related to user security and privacy. One of 
the most prevalent issues is the creation of fake profiles, 
which can lead to identity theft, cyberbullying, 
misinformation, and various other malicious activities. 
Addressing this issue requires effective detection 
methods that can accurately distinguish between 
genuine and fake profiles. To improve detection 
accuracy, our study leverages advanced machine 
learning algorithms and Natural Language Processing 
(NLP) techniques. By integrating Support Vector 
Machine (SVM) and Naïve Bayes algorithms, we aim to 
enhance the classification of fake profiles. Our proposed 
system not only addresses the limitations of traditional 
methods but also introduces a robust and adaptive 
framework capable of handling the dynamic nature of 
fake profile creation. The results demonstrate a 
significant improvement in detecting fake profiles, 
thereby contributing to safer and more trustworthy 
online environments.},
        keywords = {Fake Profile Detection,  Machine  Learning, Naïve bayes, Natural Language Processing  (NLP), Support Vector Machine (SVM).},
        month = {May},
        }