Predicting product adoption intentions: An integrated behavioral model-inspired multiview learning approach

doi:10.1016/j.im.2021.103484

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Predicting product adoption intentions: An integrated behavioral model-inspired multiview learning approach
	Zhang, Zhu1,2 ; Wei, Xuan 3; Zheng, Xiaolong1,4 ; Zeng, Daniel Dajun1,2,4
发表期刊	INFORMATION & MANAGEMENT
ISSN	0378-7206
	2021-11-01
卷号	58 期号:7 页码:12
通讯作者	Zheng, Xiaolong(xiaolong.zheng@ia.ac.cn)
摘要	Mining product adoption intentions from social media could provide insights for many business practices, such as social media marketing. Existing methods mainly focus on text information but overlook other types of data. In light of the Integrated Behavioral Model (IBM), in this study, we argue that it is valuable to consider users' social connections in addition to postings for identifying product adoption intentions. Based on this rationale, we propose a novel multiview deep learning framework to identify product adoption intentions. Extensive experiments show our proposed approach is effective, and demonstrate the benefit of incorporating social network information for intention identification.
关键词	Text mining Deep learning Product adoption intention Multi-view learning
DOI	10.1016/j.im.2021.103484
关键词[WOS]	NEURAL-NETWORKS ; SYSTEMS
收录类别	SCI
语种	英语
资助项目	Ministry of Science and Technology of China[2020AAA0108401] ; Ministry of Science and Technology of China[2019QY (Y) 0101] ; Ministry of Science and Technology of China[2020AAA0103405] ; National Natural Science Foundation of China[71974187] ; National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[71902179] ; National Natural Science Foundation of China[72074209] ; Longhua District Science and Technology Innovation Fund[10162a20200617b70da63] ; National Science Foundation[1228509]
项目资助者	Ministry of Science and Technology of China ; National Natural Science Foundation of China ; Longhua District Science and Technology Innovation Fund ; National Science Foundation
WOS研究方向	Computer Science ; Information Science & Library Science ; Business & Economics
WOS类目	Computer Science, Information Systems ; Information Science & Library Science ; Management
WOS记录号	WOS:000697698400001
出版者	ELSEVIER
七大方向——子方向分类	推荐系统
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/46056
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Zheng, Xiaolong
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Shenzhen Artificial Intelligence & Data Sci Res I, Shenzhen 518129, Peoples R China 3.Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Dept Informat Technol & Innovat, Shanghai 200030, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhang, Zhu,Wei, Xuan,Zheng, Xiaolong,et al. Predicting product adoption intentions: An integrated behavioral model-inspired multiview learning approach[J]. INFORMATION & MANAGEMENT,2021,58(7):12.
APA	Zhang, Zhu,Wei, Xuan,Zheng, Xiaolong,&Zeng, Daniel Dajun.(2021).Predicting product adoption intentions: An integrated behavioral model-inspired multiview learning approach.INFORMATION & MANAGEMENT,58(7),12.
MLA	Zhang, Zhu,et al."Predicting product adoption intentions: An integrated behavioral model-inspired multiview learning approach".INFORMATION & MANAGEMENT 58.7(2021):12.