Discovering influencers for marketing in the blogosphere

被引:76
作者
Li, Yung-Ming [1 ]
Lai, Cheng-Yang [1 ]
Chen, Ching-Wen [1 ]
机构
[1] Natl Chiao Tung Univ, Inst Informat Management, Hsinchu 300, Taiwan
关键词
Influential model; Viral marketing; Social networks; Blogosphere; Artificial neural network; NEURAL-NETWORKS; WEB; REVIEWS; BLOG; BEHAVIOR; TRUST;
D O I
10.1016/j.ins.2011.07.023
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:5143 / 5157
页数:15
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