Mining marketing knowledge to explore social network sites and online purchase behaviors
學年 103
學期 2
出版（發表）日期 2015-07-24
作品名稱 Mining marketing knowledge to explore social network sites and online purchase behaviors
作品名稱（其他語言）
著者 Liao, Shu-Hsien; Hsiao, Pei-Yuan; Li, Chien-Wen; Lin, Yun-Fei
單位 淡江大學管理科學學系
出版者 New York: Taylor & Francis Inc.
著錄名稱、卷期、頁數 Applied Artificial Intelligence 29(7), pp.679-732
摘要 Social network sites (SNS), as web-based services, allow users to make open or semiopen profiles within the systems they are part of, to see lists of other people in the group, and to see the relationships of people within different groups. As the development of Internet applications has matured, developing and evaluating business models on social network sites has become a critical issue because these sites can be an innovative source for online marketing. Most studies in Taiwan on the behavior or marketing on SNS focus on either advertising or marketing, without picturing the overall scenario. Thus, this study investigates SNS as a research subject, and explores users’ online and purchase behaviors in the cybercommunity. For this, the study uses the Apriori algorithm as an association rules approach, and cluster analysis for data mining, to categorize four kinds of online user behavior and generate purchase behavior patterns and rules. The results suggest that online users’ SNS and purchase behavior knowledge are critical for the development of online business models.
關鍵字
語言 en_US
ISSN 0883-9514
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Liao, Shu-Hsien
審稿制度 否
國別 USA
公開徵稿
出版型式 ,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/102854 )

機構典藏連結
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