Identification of Influential Customers in Social Network Based on BFO
Monica Sood1, Preetpal Kaur2

1Monica Sood, Assistant Professor, Department of CSE, IT, Lovely Professional University, Phagwara (Punjab), India.
2Preetpal Kaur, M.Tech Student, Department of CSE, IT, Lovely Professional University, Phagwara (Punjab), India.
Manuscript received on 15 April 2013 | Revised Manuscript received on 22 April 2013 | Manuscript Published on 30 April 2013 | PP: 147-149 | Volume-2 Issue-5, April 2013 | Retrieval Number: E0700042413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this paper we have proposed the implementation to identify the most influential customers in the social network. In Social network, different kind of people are communicate with each others and exchange their ideas, views about any products ,item or person. Any company or organization can increase the revenue of their product if the company identify such a customer in the social network that has the ability to influence to others in the social network . Influential customers whose connections, messages and opinion strongly influence to others in the specified social network .Such customers in the social network such as friendster, facebook can be identify by Swarm Intelligence algorithm-BFO. BFO has the strength to produce the optimal solution from the number of solution. We have followed the dataset from the social network site to find the most influential customers in the network. Bacterial Foraging Optimization(BFO) is the used to identify the optimal node in the social network .The evaluation based on the number of nodes with the highest simulation influence value to identify best nodes. Influence value based on number of friends, followers, number of messages reply, likes. The simulation influence point ratio is use to consider as the simulation influence value to identify the popular nodes in the social network with the help of optimized algorithm-BFO.
Keywords: BFO, Influential Nodes, Optimized Nodes, Swarm Intelligence.

Scope of the Article: Computer Network