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Social network analysis using big data
Author(s)
Date Issued
2016
ISBN
9789881404763
Citation
Proceedings of the International MultiConference of Engineers and Computer Scientists, 2016, vol. II.
Type
Conference Paper
Abstract
The increasing use of social networks, such as
Facebook, Twitter, and Weibo, has produced and is producing
huge volume of data. Business firms and other organizations are
interested in discovering new business insight to increase
business performance. By using advanced analytics, enterprises
can analyze big data to learn about relationships underlying
social networks that characterize the social behavior of
individuals and groups. Using data describing the relationships,
we are able to identify social leaders who influence the behavior
of others in the network, and on the other hand, to determine
which people are most affected by other network participants.
This study focuses on modeling the knowledge diffusion in
social networks. We will present a new evolving model of a
directed, scale-free network. We will test the effectiveness of
our model by a simulation using data of a real-world social network.
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