Safi Arian, H., Tarokh, M. (2018). A Knowledge Management Approach to Discovering Influential Users in Social Media. Journal of Computer & Robotics, 11(1), 69-75.
Hosniyeh Safi Arian; Mohammad Jafar Tarokh. "A Knowledge Management Approach to Discovering Influential Users in Social Media". Journal of Computer & Robotics, 11, 1, 2018, 69-75.
Safi Arian, H., Tarokh, M. (2018). 'A Knowledge Management Approach to Discovering Influential Users in Social Media', Journal of Computer & Robotics, 11(1), pp. 69-75.
Safi Arian, H., Tarokh, M. A Knowledge Management Approach to Discovering Influential Users in Social Media. Journal of Computer & Robotics, 2018; 11(1): 69-75.
A Knowledge Management Approach to Discovering Influential Users in Social Media
1Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2Associate professor, IT Group - Faculty of Industrial Engineering, K. N. Toosi University of Technology Tehran, Iran
Receive Date: 29 June 2016,
Revise Date: 21 September 2016,
Accept Date: 11 January 2017
Abstract
A key step for success of marketer is to discover influential users who diffuse information and their followers have interest to this information and increase to diffuse information on social media. They can reduce the cost of advertising, increase sales and maximize diffusion of information. A key problem is how to precisely identify the most influential users on social networks. In this paper, we propose a method to discover influential users based on knowledge management cycle that is called KMIU. The knowledge management cycle consists of several stages including capture, organize, storage, retrieval and mining stages. We try to analyze influential users in two micro bloggings networks as Facebook and twitter by KMIU method. The experimental results showed the proposed method maximize diffusion and has an accuracy 0.55. These maximization and accuracy are more than those of the previous methods.
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