期刊論文
| 學年 | 109 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2021-02-13 |
| 作品名稱 | Big data analytics of social network marketing and personalized recommendations |
| 作品名稱（其他語言） | |
| 著者 | Shu-Hsien Liao; Ching-An Yang |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Social Network Analysis and Mining 11 |
| 摘要 | A fan page is a kind of a social network. Social network marketing (SNM) is a form of Internet marketing involving the creation and sharing of content on social media networks to achieve marketing and selling goals. In addition, precise SNM requires sufficient data and analysis in terms of making accurate online recommendations. This study examines the experience of various Taiwanese fan page users utilizing a market survey, a total of 1032 valid questionnaire data, and the questionnaire is divided into five sections with 33 items in terms of a big data structure based on a relational database on the first research stage. All questions use nominal and ordinal scales. In the second stage, this study develops a personalized recommendation system (PRS) using big data analytics approach, including cluster analysis and association rules. This study shows how the research results can obtain fans behavior knowledge by examining different group profiles and develop rule-based recommendation approach to generate personalized recommendations for building a SNM mechanism. |
| 關鍵字 | Fans;Fan page;Social network marketing;Big data analytics;Personalized recommendations |
| 語言 | en |
| ISSN | 1869-5469; 1869-5450 |
| 期刊性質 | 國外 |
| 收錄於 | ESCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | AUT |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/119868 ) |