A Heterogeneous Ensemble Learning Framework for Spam Detection in Social Networks with Imbalanced Data

A Heterogeneous Ensemble Learning Framework for Spam Detection in Social Networks with Imbalanced Data

The popularity of social networks provides people with many conveniences, but their rapid growth has also attracted many attackers. In recent years, the malicious behavior of social network spammers has seriously threatened the information security of ordinary users. To reduce this threat, many rese...

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Bibliographic Details
Main Authors: Chensu Zhao, Yang Xin, Xuefeng Li, Yixian Yang, Yuling Chen
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Applied Sciences
Subjects:
online social networks
spam detection
class imbalance
ensemble learning
cost-sensitive learning
Online Access:https://www.mdpi.com/2076-3417/10/3/936

Internet

https://www.mdpi.com/2076-3417/10/3/936

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