Detecting Fake Accounts on Social Media- Instagram

Project Code :TCMAPY468

Objective

The main goal of this project is predicting the account is fake or not by analyzing the data. The dataset from Kaggle and performing Machine Learning models like Support Vector Machine and Neural Networks are used for better accuracy.

Abstract

In the present generation, online social networks (OSNs) have become increasingly popular, people’s social lives has become more associated with these sites. They use OSNs to keep in touch with each other’s, share news, organize events, and even run their own e-business. The rabid growth of OSNs and the massive amount of personal data of its subscribers have attracted attackers, and imposters to steal personal data, share false news, and spread malicious activities. On the other hand researchers have started to investigate an efficient techniques to detect abnormal activities and fake accounts relying on accounts features, and classification algorithms. However, some of the account’s exploited features have negative contribution in the final results or have no impact, also using standalone classification algorithms does not always reach satisfied results.

In this paper, a new algorithm, SVM-NN, is proposed to provide efficient detection for fake Instagram accounts, four feature selection and dimension reduction techniques were applied. Three machine learning classification algorithms were used to decide the target accounts identity real or fake, those algorithms were support vector machine (SVM), neural Network (NN), and our newly developed algorithm, SVM-NN, that uses less number of features, while still being able to correctly classify about 89% of the accounts of our training dataset SVM giving 91% accuracy

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.