Research Article Open Access

NEURO FUZZY LINK BASED CLASSIFIER FOR THE ANALYSIS OF BEHAVIOR MODELS IN SOCIAL NETWORKS

Indira Priya Ponnuvel1, Ghosh Dalim Kumar1, Kannan Arputharaj2 and Ganapathy Sannasi2
  • 1 , India
  • 2 Anna University, India
Journal of Computer Science
Volume 10 No. 4, 2014, 578-584

DOI: https://doi.org/10.3844/jcssp.2014.578.584

Submitted On: 1 September 2013 Published On: 9 December 2013

How to Cite: Ponnuvel, I. P., Kumar, G. D., Arputharaj, K. & Sannasi, G. (2014). NEURO FUZZY LINK BASED CLASSIFIER FOR THE ANALYSIS OF BEHAVIOR MODELS IN SOCIAL NETWORKS. Journal of Computer Science, 10(4), 578-584. https://doi.org/10.3844/jcssp.2014.578.584

Abstract

In this study, a new link based classifier using neuro fuzzy logic has been proposed for analyzing the social behavior based on Weblog dataset. In this system, data are processed using a multistage structure. This system provides a diagnosis using a neuro fuzzy link based classifier that analyses the user’s behavior to specific diagnostic categories based on their cluster category in social networks. It uses random walks method to organize the labels. Since the links present in the social network graph frequently represent relationships among the users with respect to social contacts and behaviours, this work observes the links of the graph in order to identify the relationships represented in the graph between the users of the social network based on some new social network metrics and the past behaviour of the users. This work is useful to provide connection between consolidated features of users based on network data and also using the traditional metrics used in the analysis of social network users. From the experiments conducted in this research work, it is observed that the proposed work provides better classification accuracy due to the application of neuro fuzzy classification method in link analysis.

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Keywords

  • Social Network
  • Neuro Fuzzy Logic
  • Link Classification