A Hybrid Machine Learning Model for Detection of Fake Profile Accounts on Social Media Networks
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Date
2024-11
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Publisher
International Journal of Engineering Research & Technology (IJERT)
Abstract
Most of us nowadays are drawn and motivated to adamantly adopt and get obsessed in every new tech-trend emerging within the social media culture that is mostly virtual, through this there is fast worldwide communication out-reach; on-screen relationships and mediated reality scenarios all over, receiving and sending everything is digital and easy to access. This has drawn the attention and motivation for this research. For instance, this massive interconnection comes with a critical challenge: the ever-growing problem of fashioning fake profile accounts. These dishonest entities, falsely reflecting themselves in auto-scripts, human imitation accounts running on bots and automatically hiding behind a masked user-identity of genuine users, can bring a substantial damage to a wide-range of connections on the internet. This encompass spam and unwanted messages to creation of fake profile accounts that lead to a variety of negative penalties such as internet being used for immoral political agendas, manipulative and misleading information to interrupt the public communication changing public opinion and subverting online communication, political processes, public health initiatives or even financial markets. Social media platforms have become breeding ground for counterfeit profiles, calling for the need for improved and reliable detection and mitigation techniques of fake profiles. This research involves the assessment and development Machine Learning model which in-turn can reveal accurately bogus social media accounts with possible mitigation methods.
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Citation
Karamu, M. B., & Araka, E. N. (2024). A hybrid machine learning model for detection of fake profile accounts on social media networks. International Journal of Engineering Research & Technology (IJERT), 13(11). https://doi.org/10.5281/zenodo.18130533