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FAKE SOCIAL MEDIA PROFILE DETECTION USING MACHINE LEARNING

Product Image: FAKE SOCIAL MEDIA PROFILE DETECTION USING MACHINE LEARNING

FAKE SOCIAL MEDIA PROFILE DETECTION USING MACHINE LEARNING

0 - Default Title
Description
In today's connected world, social media has become a vital part of our daily lives. From sharing updates and connecting with friends to exchanging ideas and accessing news, these platforms offer immense value. But alongside their popularity, a concerning issue has grown the rise of fake profiles. These accounts can be used for a variety of harmful activities spamming, phishing, spreading misinformation, manipulating opinions, or even harassing others. With millions of users online, it's nearly impossible to identify these profiles manually. This is where intelligent, automated systems come into play. This project focuses on using XGBoost (Extreme Gradient Boosting) a fast and powerful machine learning algorithm that is used to detect fake social media profiles. XGBoost is well-known for handling structured data and performing better than many traditional models, thanks to its boosting technique and inbuilt regularization that helps prevent overfitting. To train the model, we used a dataset containing various features gathered from public user profiles.
Product details
Binding:
Paperback
Number of Pages:
52
Release Date:
2025-05-13
Publication Date:
2025-05-13
Publisher:
LAP LAMBERT Academic Publishing
Languages:
Original: English
ISBN10:
620843663X
ISBN13:
9786208436636
GPSR Manufacturer Reference:
Weight:
96 g
Height:
150 cm
Width:
220 cm
Thickness:
4 cm
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