Fake Profile Detection Using Machine Learning
Objective of this project is to develop a robust and efficient system for the detection of fake Instagram accounts, leveraging the power of machine learning techniques. By analyzing a meticulously curated dataset, derived from authentic social accounts, the project aims to explore key indicators and patterns that distinguish genuine accounts from fake ones. The dataset incorporates a range of pertinent features, including follower-following ratios, user biography length, follower and following counts, profile picture presence, account privacy status, media content count, and various attributes related to the username.
Fake Account Detection with Neural Networks addresses the pervasive issue of fraudulent accounts in online platforms. Utilizing the capabilities of neural networks, this system analyzes user behavior, engagement patterns, and content to identify indicators of fake accounts. By continuously learning from evolving online dynamics, the model distinguishes between genuine and fake profiles, contributing to the mitigation of online fraud, identity theft, and the spread of misinformation in digital spaces.
Detecting Fake Accounts on Social Media using Python
Software Requirements :-
- Coding Language : Python
- Implementation: Website Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : HTML, CSS, JavaScript, Django
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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