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Personality or Value: A Comparative Study of Psychographic Segmentation Based on an Online Review Enhanced Recommender System

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成果类型:
期刊论文
作者:
Liu, Hui;Huang, Yinghui;Wang, Zichao;Liu, Kai;Hu, Xiangen;...
通讯作者:
Wang, Weijun
作者机构:
[Huang, Yinghui; Wang, Weijun; Hu, Xiangen; Liu, Hui; Liu, Kai] Cent China Normal Univ, Minist Educ, Key Lab Adolescent Cyberpsychol & Behav, Wuhan 430079, Hubei, Peoples R China.
[Huang, Yinghui] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
[Wang, Zichao] Rice Univ, Dept Elect & Comp Engn, Houston, TX 77005 USA.
[Hu, Xiangen] Univ Memphis, Dept Psychol, Memphis, TN 38152 USA.
通讯机构:
[Wang, Weijun] C
Cent China Normal Univ, Minist Educ, Key Lab Adolescent Cyberpsychol & Behav, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
Big data-drivenmarketing;Lexicon construction;Online review;Psychographic segmentation;Recommender system;User preference prediction
期刊:
Applied Sciences-Basel
ISSN:
2076-3417
年:
2019
卷:
9
期:
10
页码:
1992
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [71571084, 71271099]; China Scholarship CouncilChina Scholarship Council
机构署名:
本校为第一且通讯机构
院系归属:
心理学院
信息管理学院
摘要:
Big consumer data promises to be a game changer in applied and empirical marketing research. However, investigations of how big data helps inform consumers' psychological aspects have, thus far, only received scant attention. Psychographics has been shown to be a valuable market segmentation path in understanding consumer preferences. Although in the context of e-commerce, as a component of psychographic segmentation, personality has been proven to be effective for prediction of e-commerce user preferences, it still remains unclear whether psyc...

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