政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/75525

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政大機構典藏 > 商學院 > 企業管理學系 > 期刊論文 > Item 140.119/75525

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题名:	Predicting the influence of users` posted information for eWOM advertising in social networks
作者:	Chen, Y.-L.;Tang, Kwei;Wu, C.-C. 唐揆
贡献者:	企管系
关键词:	Social networking (online);Electronic wordof-mouth (eWOM);Influence;Sentiment analysis;Data mining
日期:	2014-11
上传时间:	2015-06-02 17:10:41 (UTC+8)
摘要:	Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users` posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post`s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.
關聯:	Electronic Commerce Research and Applications, 13(6), 431-439
数据类型:	article
DOI 連結:	http://dx.doi.org/10.1016/j.elerap.2014.10.001
DOI:	10.1016/j.elerap.2014.10.001
显示于类别:	[企業管理學系] 期刊論文

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