• Sai Sindhu V
• Tejovathi S
• Lokapavani S
• Ravi Paavana
• Pavan kumar U

The main objective behind developing this project is to detect the frauds on social media Networks. This days, social media has a significant impact on everyone’s life. Most people frequently utilize social media platforms such as Facebook, Twitter, Instagram. To determine who poses threats on these platforms, it is necessary to distinguish between the real and fake social media profiles. In this study identifying fake accounts utilizing 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, in this study a variety of Python and the necessary libraries, such as SK learn, Numpy, and Pandas are used and XG Boost is the best machine learning technique for finding fake profiles.

Implementation of Fraud Detection on Social Media Networking Websites using Machine Learning

"Implementation of Fraud Detection on Social Media Networking Websites using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.180-187, June-2024, Available :http://www.jetir.org/papers/JETIRGJ06028.pdf

"Implementation of Fraud Detection on Social Media Networking Websites using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp180-187, June-2024, Available at : http://www.jetir.org/papers/JETIRGJ06028.pdf