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@article{176090,
        author = {Vikrant Chandrakant Kothimbire and Vinayak Makwana and Vaishnavi Gaikwad and Vaishnavi Panchal},
        title = {Safeguarding social media: Fake profile detection on Instagram using ML},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {4926-4931},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176090},
        abstract = {Social media has become a major way for people to communicate, share content, and stay connected. However, the rise of fake accounts on platforms like Instagram is a growing concern. These fake profiles can spread misinformation, scam users, and harm online communities. This project aims to detect fake profiles using machine learning techniques.
We use three popular algorithms—Support Vector Machine (SVM), Random Forest, and Decision Tree—to classify user accounts as either real or fake. The models are trained on a dataset that includes user activity, engagement levels, and content features.
Our main goal is to compare how well each model can identify fake accounts. The results show that machine learning can be a powerful tool in improving safety and trust on social media. This research also suggests future directions, such as combining more data types and applying the system to other platforms.},
        keywords = {Fake accounts, Social media, Machine learning, SVM, Random Forest, Decision Tree, Online safety, User behavior, Data analysis.},
        month = {April},
        }