Using Deep Learning for Community Discovery in Social Networks

Author(s):  
Di Jin ◽  
Meng Ge ◽  
Zhixuan Li ◽  
Wenhuan Lu ◽  
Dongxiao He ◽  
...  
2020 ◽  
pp. 114536
Author(s):  
Weimin Li ◽  
Heng Zhu ◽  
Shaohua Li ◽  
Hao Wang ◽  
Hongning Dai ◽  
...  

Author(s):  
Putra Wanda ◽  
Marselina Endah Hiswati ◽  
Huang J. Jie

Manual analysis for malicious prediction in Online Social Networks (OSN) is time-consuming and costly. With growing users within the environment, it becomes one of the main obstacles. Deep learning is growing algorithm that gains a big success in computer vision problem. Currently, many research communities have proposed deep learning techniques to automate security tasks, including anomalous detection, malicious link prediction, and intrusion detection in OSN. Notably, this article describes how deep learning makes the OSN security technique more intelligent for detecting malicious activity by establishing a classifier model.


2016 ◽  
Vol 106 (8) ◽  
pp. 1213-1241 ◽  
Author(s):  
Giulio Rossetti ◽  
Luca Pappalardo ◽  
Dino Pedreschi ◽  
Fosca Giannotti

2018 ◽  
Vol 48 (11) ◽  
pp. 4232-4246 ◽  
Author(s):  
Di Xue ◽  
Lifa Wu ◽  
Zheng Hong ◽  
Shize Guo ◽  
Liang Gao ◽  
...  

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