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@article{178619,
        author = {Aakif Mohamed Nadeem and Ms. Alina Raheen and Sadiya Mohammedi and Mohammed Ismail and Bandi Raghavendra and Shaik Akram},
        title = {FAKE SOCIAL MEDIA PROFILE DETECTION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4146-4154},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178619},
        abstract = {These days, social media has a significant impact on everyone’s life. Most people frequently utilize social media platforms. Each of these social media platforms offers benefits and drawbacks, as well as security risks for our information. To determine who poses threats on these platforms, it is necessary to distinguish between the real and fake social media profiles. There are traditionally used various methods for identifying fake social media accounts. But these platforms need to be better at identifying phoney accounts. The accuracy rate of identifying fake accounts utilizing timestamp data types is improved in this proposed work employing high gradient boosting algorithms and Natural Language Processing. In order to investigate the relationship between various machine learning methods and multi-features in time series, this study employs a variety of machine learning techniques.},
        keywords = {Fake profiles, Machine learning methods, Natural Language Processing (NLP), Timestamp, Extreme Gradient Boosting algorithm.},
        month = {May},
        }