Identifying influential reviewers for word-of-mouth marketing

被引：82

作者：

Li, Yung-Ming ^{[1
]}

Lin, Chia-Hao ^{[1
]}

Lai, Cheng-Yang ^{[1
]}

机构：

[1] Natl Chiao Tung Univ, Inst Informat Management, Hsinchu 300, Taiwan

来源：

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS | 2010年 / 9卷 / 04期

关键词：

Word-of-mouth marketing; Social network; Opinion mining; Trust; RFM; PMI; SERVICES; SYSTEM; TRUST; WEB;

D O I：

10.1016/j.elerap.2010.02.004

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The key to word-of-mouth marketing is to discover the potential influential nodes for efficiently spreading product impressions. In this paper, a framework combined with mining techniques, a modified PMI measure, and an adaptive RFM model is proposed to evaluate the influential power of online reviewers. An artificial neural network is adopted to identify the target reviewers and a well-developed trust mechanism is utilized for effectiveness evaluation. This proposed framework is verified by the data collected from Epinions.com, one of the most popular online product review websites. The experimental results show that the proposed model could accurately identify which reviewers to select to become the influential nodes. This proposed approach can be exploited in effectively carrying out online word-of-mouth marketing, which can save a lot of resources in finding customers. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：294 / 304

页数：11

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