Mgephi : Modified Gephi for Effective Social Network Analysis

Authors(2) :-Dr. M.Thangaraj, S. Amutha

One of the most visible trends on the web is the emergence of social web sites, which is help people create and gather knowledge by simplifying user contribution via blogs, tagging and folksonomies, wikis, podcasts and online Social Networks. Social Network Analysis network can be very large containing from thousands to even millions of nodes. The sheer number of nodes and links makes drawing the entire network computationally infeasible. SNA tools are used find the Ranking, Partitions, and Layouts with various algorithms, visualization, Statistics and Filters the nodes and edges in the large type of datasets and done Network Analysis module, Permutation hierarchy and fisheye transformation etc. The feature performed in Modified Gephi framework. In this paper, a new framework is proposed for an effective Social Network Analysis. The framework is implementing for measuring the performance. The performance measures show remarkable improvement over their existing methods.

Authors and Affiliations

Dr. M.Thangaraj
Department of Computer Science/Madurai Kamaraj University/Madurai, Tamil Nadu, India
S. Amutha
Department of Computer Science/Manonmanian Sundaranar University/Tirunelveli, Tamil Nadu, India

Social Network Analysis, Gephi, Pajek, NodeXL, Partition, Visualization, FishEye Transformation.

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 39-50
Manuscript Number : CSEIT1726334
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Dr. M.Thangaraj, S. Amutha, "Mgephi : Modified Gephi for Effective Social Network Analysis", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.39-50, January-February.2018
URL : http://ijsrcseit.com/CSEIT1726334

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