Fake Profile Detection on Social-Media


  • Shamim Ahmad Student, Department of Computer science & Engineering, Integral University Lucknow, INDIA
  • Dr. Manish Madhava Tripathi Professor, Department of Computer science & Engineering, Integral University Lucknow, INDIA




Random Forest, XG-Boost, NN, Social Media, Fake Profile


In this generation, social media platforms  such  as  Twitter, Instagram, Linkedln, and others play an important role in our everyday lives. The whole world is actively involved. However, it must  also  address the problem of  false profiles. The majority of fake pattern are generated by human or robots or cyborgs built to spread for misinformation, data piracy and identity theft. Therefore, In this article, we will discuss a model name as Detection of fake profile on social media model, which will be differentiate between fake and real profile on twitter based on visible features like, friend counts, follower counts, status counts, and more by using various machine learning classification methods. The dataset will be used twitter profile and we will Taking the Machine learning classification model like, Neural Network (NN), Random Forest, XG-Boost, and LSTM for determining the authenticity of a social media profile and for used implementation language is Python3 along with all the required libraries like, pandas, NumPy, and Sklearn etc.


Download data is not yet available.



How to Cite

Shamim Ahmad, & Dr. Manish Madhava Tripathi. (2023). Fake Profile Detection on Social-Media. International Journal of Engineering and Management Research, 13(3), 262–265. https://doi.org/10.31033/ijemr.13.3.37