| dc.contributor | 企管系 | |
| dc.creator (作者) | Chen, Y.-L.;Tang, Kwei;Wu, C.-C. | |
| dc.creator (作者) | 唐揆 | zh_TW |
| dc.date (日期) | 2014-11 | |
| dc.date.accessioned | 2-Jun-2015 17:10:41 (UTC+8) | - |
| dc.date.available | 2-Jun-2015 17:10:41 (UTC+8) | - |
| dc.date.issued (上傳時間) | 2-Jun-2015 17:10:41 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/75525 | - |
| dc.description.abstract (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. | |
| dc.format.extent | 707347 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Electronic Commerce Research and Applications, 13(6), 431-439 | |
| dc.subject (關鍵詞) | Social networking (online); Electronic wordof-mouth (eWOM); Influence; Sentiment analysis; Data mining | |
| dc.title (題名) | Predicting the influence of users` posted information for eWOM advertising in social networks | |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1016/j.elerap.2014.10.001 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1016/j.elerap.2014.10.001 | |
