Detecting Product Adoption Intentions via Multiview Deep Learning

doi:10.1287/ijoc.2021.1083

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

	Detecting Product Adoption Intentions via Multiview Deep Learning
	Zhang, Zhu1,2 ; Wei, Xuan 3; Zheng, Xiaolong1,2,4 ; Li, Qiudan1,2 ; Zeng, Daniel Dajun1,2,4
发表期刊	INFORMS JOURNAL ON COMPUTING
ISSN	1091-9856
	2021-09-14
页码	17
通讯作者	Zheng, Xiaolong(xiaolong.zheng@ia.ac.cn)
摘要	Detecting product adoption intentions on social media could yield significant value in a wide range of applications, such as personalized recommendations and targeted marketing. In the literature, no study has explored the detection of product adoption intentions on social media, and only a few relevant studies have focused on purchase intention detection for products in one or several categories. Focusing on a product category rather than a specific product is too coarse-grained for precise advertising. Additionally, existing studies primarily focus on using one type of text representation in target social media posts, ignoring the major yet unexplored potential of fusing different text representations. In this paper, we first formulate the problem of product adoption intention mining and demonstrate the necessity of studying this problem and its practical value. To detect a product adoption intention for an individual product, we propose a novel and general multiview deep learning model that simultaneously taps into the capability of multiview learning in leveraging different representations and deep learning in learning latent data representations using a flexible nonlinear transformation. Specifically, the proposed model leverages three different text representations from a multiview perspective and takes advantage of local and long-term word relations by integrating convolutional neural network (CNN) and long short-term memory (LSTM) modules. Extensive experiments on three Twitter datasets demonstrate the effectiveness of the proposed multiview deep learning model compared with the existing benchmark methods. This study also significantly contributes research insights to the literature about intention mining and provides business value to relevant stakeholders such as product providers.
关键词	web mining business intelligence intention detection deep learning social media analytics
DOI	10.1287/ijoc.2021.1083
关键词[WOS]	SEARCH
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] ; Science Fund for Creative Research Groups of the National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[71472175] ; National Natural Science Foundation of China[71974187] ; National Natural Science Foundation of China[61671450] ; National Natural Science Foundation of China[71902179] ; National Natural Science Foundation of China[72074209] ; National Natural Science Foundation of China[71825007] ; Strategic Priority Research Pro-gram of Chinese Academy of Sciences[XDA27030100] ; Research Foundation of SKL-MCCS for Young Scientists[20190212] ; Longhua District Science and Technology Innovation Fund[10162a20200617b70da63] ; National Science Foundation[1228509]
项目资助者	Ministry of Science and Technology of China ; Science Fund for Creative Research Groups of the National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Pro-gram of Chinese Academy of Sciences ; Research Foundation of SKL-MCCS for Young Scientists ; Longhua District Science and Technology Innovation Fund ; National Science Foundation
WOS研究方向	Computer Science ; Operations Research & Management Science
WOS类目	Computer Science, Interdisciplinary Applications ; Operations Research & Management Science
WOS记录号	WOS:000708981400001
出版者	INFORMS
七大方向——子方向分类	推荐系统
引用统计	被引频次：6[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/173211/46231
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 ofManagement & Control Complex Syst, Beijing 100190, Peoples R China 2.Shenzhen Artificial Intelligence & Data Sci Inst, 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. Detecting Product Adoption Intentions via Multiview Deep Learning[J]. INFORMS JOURNAL ON COMPUTING,2021:17.
APA	Zhang, Zhu,Wei, Xuan,Zheng, Xiaolong,Li, Qiudan,&Zeng, Daniel Dajun.(2021).Detecting Product Adoption Intentions via Multiview Deep Learning.INFORMS JOURNAL ON COMPUTING,17.
MLA	Zhang, Zhu,et al."Detecting Product Adoption Intentions via Multiview Deep Learning".INFORMS JOURNAL ON COMPUTING (2021):17.