This repository contains the code for the paper titled "A Survey on Machine Learning Algorithms for Detecting Fake Instagram Accounts", which has been published in the proceedings of the 3rd IEEE International Conference on Advances in Computing, Communication Control and Networking (ICACCCN). (Click here to read the research paper)
This paper proposed the use of supervised machine learning algorithms to classify Instagram profiles as fake or real. It uses the data collected from 1000 Instagram profiles, using Instagram scraping. The classification was successfully performed with a highest accuracy of 98% obtained from RandomForest.
The following machine learning algorithms were used for performing sentiment analysis:
- RandomForest
- Multi Layer Perceptron
- AdaBoost
- Artificial Neural Network
- Stochastic Gradient Descent
Authors: Harish Balasubramaniam, Zeel Desai, Karishma Anklesaria, Dr. Vikram Kulkarni