Title: Discovering influencers for marketing in the blogosphere
Authors: Li, Yung-Ming
Lai, Cheng-Yang
Chen, Ching-Wen
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
Keywords: Influential model;Viral marketing;Social networks;Blogosphere;Artificial neural network
Issue Date: 1-Dec-2011
Abstract: Discovering influential bloggers will not only allow us to understand better the social activities taking place in the blogosphere, but will also provide unique opportunities for sales and advertising. In this paper, we develop an MIV (marketing influential value) model to evaluate the influential strength and identify the influential bloggers in the blogosphere. We analyze three dimensions of blog characteristics (network-based, content-based, and activeness-based factors) and utilize an artificial neural network (ANN) to discover potential bloggers. Based on peer and official evaluations, the experimental results show that the proposed framework outperforms two social-network-based methods (out-degree and betweenness centrality algorithms) and two content-based mechanisms (review rating and popular author approaches). The proposed framework can be effectively applied to support marketers or advertisers in promoting their products or services. (C) 2011 Elsevier Inc. All rights reserved.
URI: http://dx.doi.org/10.1016/j.ins.2011.07.023
http://hdl.handle.net/11536/14642
ISSN: 0020-0255
DOI: 10.1016/j.ins.2011.07.023
Journal: INFORMATION SCIENCES
Volume: 181
Issue: 23
Begin Page: 5143
End Page: 5157
Appears in Collections:Articles


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