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@article{150525,
        author = {Gayatri Nair and Shraddha Gupta and Kajal Dewade and Vaibhav Davande and P.R.Kulkarni},
        title = {Detection of Fake Twitter Accounts with Machine Learning Algorithms},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {7},
        pages = {120-123},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=150525},
        abstract = {Social networks have become a part of human life in many areas today.  Many activities such as communication, promotion, advertisement, news and agenda have been started to be carried out over social networks.  Some malicious accounts on Twitter are used for purposes such as creating false information and agenda.  This is one of the main problems in social networks.  Therefore, it is important to detect malicious accounts.  In this study, machine learning-based methods were used to detect fake accounts that could mislead people.  The dataset created for this purpose was pre-processed and fake accounts were detected by machine learning algorithms.  Decision tree, logistic regression and support vector machine algorithms are used to detect fake accounts.  The classification success of these methods has been compared and it has been proven that logistic regression gives more successful results.},
        keywords = {Social Networks, Twitter, Bot Detection, Advanced Machine Learning, Classification.},
        month = {},
        }