• PUNUGOTI SATHVIKA
• V RAJINI
• GOURAVARAM KAVYA
• SNOBER IQBAL

In today's digital era, where social media has become deeply ingrained in our daily lives, the task of identifying fake accounts on platforms like Instagram has emerged as a critical challenge. Addressing this issue head-on is the "Instagram Fake Account Detection using Machine Learning" project, which relies on Python as its primary toolset. This initiative harnesses the power of two prominent machine learning algorithms, namely the Random Forest Classifier and the Decision Tree Classifier, to tackle the problem effectively. The Random Forest Classifier exhibits exceptional performance, boasting a perfect accuracy of 100% on the training dataset and an impressive 93% accuracy on the test dataset. Similarly, the Decision Tree Classifier showcases its efficacy with a training accuracy of 92% and a corresponding test accuracy of 92%. The dataset utilized in this project comprises 576 records, each characterized by 12 distinct features. These features encapsulate crucial attributes of Instagram profiles, ranging from the presence of a profile picture to the privacy status of accounts. Other factors considered include the composition of usernames and full names, the length of user bios, the presence of external URLs, and various metrics related to account activity such as post count, follower count, and following count. Ultimately, each account is classified as either "Fake" or "Not" based on these features. Through the utilization of Python and advanced machine learning models, this project aims to offer a robust and efficient solution for detecting fake Instagram accounts. By doing so, it contributes significantly to upholding the platform's integrity and safeguarding the security of its user base.

Social media, Instagram, Fake accounts, Machine learning, Python, Random Forest Classifier, Decision Tree Classifier, Dataset, Features, User interaction, Security, Online threats, Support Vector Machine, Convolutional Neural Network, Cyberbullying

"FAKE PROFILE DETECTION ON SOCIAL NETWORKING WEBSITES USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.m676-m681, April-2024, Available :http://www.jetir.org/papers/JETIR2404C87.pdf

"FAKE PROFILE DETECTION ON SOCIAL 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 4, page no. ppm676-m681, April-2024, Available at : http://www.jetir.org/papers/JETIR2404C87.pdf