• BURIDI AMRUTHA
• KOYYANA RAMYA
• VANAPALLI SOWJANYA
• YAMALA KARTHEEK
• YEGIREDDI PRAVEEN

Online social media is taking over the globe these days in a number of ways. The amount of people utilizing social media is rapidly rising every day. The primary benefit of social media on the internet is the ease with which we can connect with others and improve our communication with them. This opened up additional avenues for possible attacks, such impersonation and fraudulent information. According to a recent poll, there are far more social media accounts than there are users. This may indicate a rise in phony accounts in recent years. It is challenging for online social media platforms to recognize these fraudulent profiles. Due to the abundance of misleading material and marketing on social media, it is necessary to recognize these bogus accounts. Traditional techniques are unable to reliably differentiate between authentic and fraudulent accounts. The earlier efforts are out of date due to advancements in the creation of false accounts. In order to detect phony accounts, the new models employed a variety of strategies, including automated posting and comments, disseminating misleading material, and bombarding users with spam. As the number of phony accounts on the rise, many algorithms with various features are being used. Algorithms such as Naïve Bayes, Support Vector Machine, and Random Forest, which were once used, are no longer effective in identifying fraudulent accounts. We developed a novel technique in this study to distinguish phony accounts. We used the gradient boosting technique to a three-attribute decision tree. These characteristics include fake activity, engagement rate, and spam comments. We used data science and machine learning together to precisely.

Machine learning, fake account detection, ANN, Python.

"FAKE SOCIAL MEDIA ACCOUNT DETECTION USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.d399-d403, May-2024, Available :http://www.jetir.org/papers/JETIR2405342.pdf

"FAKE SOCIAL MEDIA ACCOUNT DETECTION USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppd399-d403, May-2024, Available at : http://www.jetir.org/papers/JETIR2405342.pdf