Detecting spammers on social network through clustering technique

The vast usage of social media makes it a familiar platform for malicious users referred as social spammers to overwhelm usual users with unwanted content. One efficient way for detection of social spammer is to construct a classifier based on social network and content information. However social spammers are adaptable and sophisticated to game the system with rapidly developing network and content patterns. The spammer detection is always a challenging issue on social network. The rigid anti spam norms have resulted in development of spammers. They look alike legal users who are difficult to recognize. In this study a novel spammer classification method based on LDA (Latent Dirichlet Allocation) a topic model is proposed. This method retrieves both the global and local data of topic distribution patterns which seizes the spamming essence. The method is tested on one dataset of benchmark and one self-gathered data set. This proposed approach outperforms other state of art approaches in terms of average FI-score.

[1]  Ashish Bindra,et al.  SocialLDA: Scalable Topic Modeling in Social Networks , 2012 .

[2]  Zhiwu Lu,et al.  Community Based Spammer Detection in Social Networks , 2015, WAIM.

[3]  Ali Selamat,et al.  Improved email spam detection model with negative selection algorithm and particle swarm optimization , 2014, Appl. Soft Comput..

[4]  Meet Rajdev,et al.  Fake and Spam Messages: Detecting Misinformation During Natural Disasters on Social Media , 2015, 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT).

[5]  Surendra Sedhai,et al.  Semi-Supervised Spam Detection in Twitter Stream , 2017, IEEE Transactions on Computational Social Systems.

[6]  Weiqing Sun,et al.  Efficient spam detection across Online Social Networks , 2016, 2016 IEEE International Conference on Big Data Analysis (ICBDA).

[7]  Hong Wang,et al.  Sparse network embedding for community detection and sign prediction in signed social networks , 2017, Journal of Ambient Intelligence and Humanized Computing.

[8]  Yao Lu,et al.  Detecting “Smart” Spammers on Social Network: A Topic Model Approach , 2016, NAACL.

[9]  Junbin Gao,et al.  Image Spam Classification Using Neural Network , 2015, SecureComm.

[10]  Naveed Mastan Md Abdul,et al.  A Survey on LDA Approach in Predicting Link Behavior in Social Networks , 2015 .

[11]  Xianghan Zheng,et al.  A novel method for spammer detection in social networks , 2015, 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM).

[12]  Li Zhang,et al.  Hybrid decision tree and naïve Bayes classifiers for multi-class classification tasks , 2014, Expert Syst. Appl..

[13]  Zheyi Chen,et al.  Detecting spammers on social networks , 2015, Neurocomputing.

[14]  Cao Xiao,et al.  Detecting Clusters of Fake Accounts in Online Social Networks , 2015, AISec@CCS.

[15]  Azmi Jaafar,et al.  A Mapping Study to Investigate Spam Detection on Social Networks , 2017 .

[16]  Sarunas Girdzijauskas,et al.  Adaptive Graph-based algorithms for Spam Detection in Social Networks , 2016 .

[17]  Sumaiya Pathan,et al.  Detection of Spam Messages in Social Networks based on SVM , 2016 .

[18]  Krishna P. Gummadi,et al.  Towards Detecting Anomalous User Behavior in Online Social Networks , 2014, USENIX Security Symposium.

[19]  Mehrdad Jalali,et al.  Spam detection in social networks: A review , 2015, 2015 International Congress on Technology, Communication and Knowledge (ICTCK).

[20]  Aakanksha Saini,et al.  DISCERNING SPAM IN SOCIAL NETWORKING SITES , 2016 .

[21]  Harshal S. Multani,et al.  Spam Detection in Social Media Networks: A Data Mining Approach , 2015 .

[22]  Fangzhao Wu,et al.  Co-detecting social spammers and spam messages in microblogging via exploiting social contexts , 2016, Neurocomputing.

[23]  Xia Feng,et al.  Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey , 2017, Multimedia Tools and Applications.

[24]  Rishabh Kaushal,et al.  Improving spam detection in Online Social Networks , 2015, 2015 International Conference on Cognitive Computing and Information Processing(CCIP).

[25]  Ioannis Korkontzelos,et al.  Detection of spam-posting accounts on Twitter , 2018, Neurocomputing.

[26]  James Caverlee,et al.  Detecting Spam URLs in Social Media via Behavioral Analysis , 2015, ECIR.