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IJSTR >> Volume 7 - Issue 1, January 2017 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Extraction & Visualization Of Social Relations On Social Networking Services Using Association Rule Mining

[Full Text]

 

AUTHOR(S)

Mayuri R. Tone, M. B. Gudadhe

 

KEYWORDS

Information diffusion, influence, social media, social network analysis.

 

ABSTRACT

Social media and Social Network Analysis (SNA) acquired a huge popularity and represent one of the most important social and computer science phenomena of recent years. One of the most studied problems in this research area is influence and information propagation. The aim of this paper is to analyze the information diffusion process and predict the influence (represented by the rate of infected nodes at the end of the diffusion process) of an initial set of nodes in two networks: Facebook users contacts users commenting these posts. These networks are dissimilar in their structure (size, type, diameter, density, components), and the type of the Relationships (explicit relationship represented by the contacts links, and implicit relationship created by commenting on post), they are extracted using Node XL tool. Three models are used for modeling the dissemination process: Linear Threshold Model (LTM), Independent Cascade Model (ICM) and an extension of this last called Weighted Cascade Model (WCM). Networks metrics and visualization were manipulated By Node Xl. Experiments results show that the structure of the network affects the diffusion process directly. Unlike results given in the blog world networks, the information can spread farther through explicit connections than through implicit relations.

 

REFERENCES

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