International Journal of Wireless and Microwave Technologies(IJWMT)

ISSN: 2076-1449 (Print), ISSN: 2076-9539 (Online)

Published By: MECS Press

IJWMT Vol.5, No.4, Jul. 2015

Enhanced Techniques for Filtering of Wall Messages over Online Social Networks (OSN) User Profiles

Full Text (PDF, 583KB), PP.47-61

Views:51   Downloads:1


Nikhil Sanyog Choudhary, Himanshu Yadav, Anurag Jain

Index Terms

OSN;SVM;FCM;J48 Classifier;Filtering Rules


Online Social Networks enables various users to connect and share their messages publicly and privately. On one hand it provides advantages to the users to connect and share but on the other hand it provides disadvantage of being attacks or post messages which contains negative or abuse words. Hence OSN provides various filtering rules for security against these wall messages. Although there are various filtering rules and classifiers implemented for the filtering of these users wall messages in popular OSN such as Twitter and Facebook. But in the proposed methodology not only filtering of these wall messages is done but the categorization of normal or negative messages are identified and hence on the basis users can be blacklisted. The proposed methodology is compared with FCM and SVM for clustering and classification of messages. This approach efficiently categorizes the messages but restricts for generating filtering rules and blacklist management. Thus the approach with FCM and J48 first initializes clustering using FCM followed by generation of rules using J48 based decision tree. Hence on the basis of the rules generated message are classified and message which doesn't contain attacks is then filtered on the basis of dictionary which contains a list of abuse words. The methodology is implemented by applying FCM and SVM and a comparison is done with FCM and J48 for the performance on the basis of accuracy to detect abnormal messages.

Cite This Paper

Nikhil Sanyog Choudhary, Himanshu Yadav, Anurag Jain,"Enhanced Techniques for Filtering of Wall Messages over Online Social Networks (OSN) User Profiles", IJWMT, vol.5, no.4, pp.47-61, 2015.DOI: 10.5815/ijwmt.2015.04.05


[1]Walter Willinger, Reza Rejaie, Mojtaba Torkjazi, Masoud Valafar and Mauro Maggioni, "Research on Online Social Networks: Time to Face the Real Challenges", 2009.

[2]Alan Mislove, Massimiliano Marcon, Krishna P. Gummadi, Peter Druschel and Bobby Bhattacharjee, "Measurement and Analysis of Online Social Networks", ACM, 2007.

[3]Qiang Wang, Yi Guan and Xiaolong Wang "SVM-Based Spam Filter with Active and Online Learning", 2003.

[4]Gordon V. Cormack, José María Gómez Hidalgo and Enrique Puertas Sanz "Spam Filtering for Short Messages", ACM, 2007.

[5]M. Vanetti, E. Binaghi, E. Ferrari, B. Carminatti and M. Carullo "A System to Filter Unwanted Messages from OSN User Walls", IEEE Transactions on Knowledge and Data Engineering, 2013.

[6]James C. Bezdek, Robert Ehrlich, William Full, "FCM-The Fuzzy C-Means Clustering Algorithm", Computers & Geosciences Vol. 10, No. 2-3, pp. 191-203, 1984.

[7]Rui Xu and Donald Wunsch "Survey of Clustering Algorithms", IEEE Transactions on Neural Networks, 2005.

[8]M.S. Yang "A Survey of Fuzzy Clustering", Mathl. Comput. Modelling, 1993.

[9]S.V.N. Vishwanathan and M. Narasimha Murty "SSVM: A Simple SVM Algorithm", 2002.

[10]Jie Tang, Jimeng Sun, Chi Wang and Zi Yang, "Social Influence Analysis in Large-scale Networks" KDD'09, June 28–July 1, ACM, 2009.

[11]F. Liu and H. J. Lee "Use of Social Network Information to Enhance Collaborative Filtering Performance" Expert Systems with Applications, Science Direct, Elsevier Ltd.-2009.

[12]O. Kafali, A. Gunay and P. Golum "Detecting and Predicting Privacy Violations in OSN" Distributed Parallel Database, Springer Science, 2013.

[13]P. Oscar Boykin and Vwani P. Roy chowdhury. "Leveraging social networks to fight spam" Computer, 38(4):61–68, 2005.

[14]Vaishali Bhujade and N. J. Janwe "Knowledge Discovery in Text Mining Technique Using Association Rules Extraction", International Conference on Computational Intelligence and Communication Systems, 2011.

[15]M. Chau and H. Chen "A Machine Learning Approach to Web Page Filtering using Content and Structure Analysis" Decision Support Systems, Science Direct, Elsevier B.V. 2007, doi:10.1016/j.dss.2007.06.002.

[16]Michelle Madejski, Maritza Johnson and Steven M. Bellovin "A Study of Privacy Settings Errors in an Online Social Network", 2011.

[17]N. Kanya and S. Geetha "Information Extraction -A Text Mining Approach", ICTES 2007.

[18]Andrew McCallum, Kamal Nigam and Lyle H. Ungar "Efficient Clustering of High Dimensional Data Sets with Application to Reference Matching", 2000.

[19]Weiling Cai, Songcan Chen and Daoqiang Zhang "Fast and Robust Fuzzy C-Means Clustering Algorithms Incorporating Local Information for Image Segmentation", 2004.

[20]A. Banumathi and A. Pethalakshmi "Increasing Cluster Uniqueness in Fuzzy C-Means through Affinity Measure", Proceedings of the International Conference on Pattern Recognition, Informatics and Medical Engineering, IEEE, 2012.