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Unveiling the Hidden Truth of Drug Addiction: A Social Media Approach Using Similarity Network-Based Deep Learning

文献类型：期刊论文

作者Xie, Jiaheng1; Zhang, Zhu2,5; Liu, Xiao4; Zeng, Daniel2,3,5
刊名JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
出版日期2021-01-02
卷号38期号:1页码:166-195
关键词Computational design science deep learning social media analytics health IT HealthTech opioid addiction addiction treatment
ISSN号0742-1222
DOI10.1080/07421222.2021.1870388
通讯作者Xie, Jiaheng(jxie@udel.edu)
英文摘要Opioid use disorder (OUD) is an epidemic that costs the U.S. healthcare systems $504 billion annually and poses grave mortality risks. Existing studies investigated OUD treatment barriers via surveys as a means to mitigate this opioid crisis. However, the response rate of these surveys is low due to social stigma around opioids. We explore user-generated content in social media as a new data source to study OUD. We design a novel IT system, SImilarity Network-based DEep Learning (SINDEL), to discover OUD treatment barriers from patient narratives and address the challenge of morphs. SINDEL significantly outperforms state-of-the-art NLP models, reaching an F1 score of 76.79 percent. Thirteen types of treatment barriers were identified and verified by domain experts. This work contributes to information systems with a novel deep-learning-based approach for text analytics and generalized design principles for social media analytics methods. We also unveil the hurdles patients endure during the opioid epidemic.
资助项目Ministry of Science and Technology of China[2020AAA0108401] ; Ministry of Science and Technology of China[2017YFC0820105] ; Ministry of Science and Technology of China[2019QY(Y)0101] ; Ministry of Science and Technology of China[2020AAA0103405] ; Ministry of Health of China[2017ZX10303401-002] ; National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[72074209] ; National Natural Science Foundation of China[71974187] ; National Natural Science Foundation of China[71472175] ; National Science Foundation[1228509]
WOS研究方向Computer Science ; Information Science & Library Science ; Business & Economics
语种英语
WOS记录号WOS:000636054300008
出版者ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
资助机构Ministry of Science and Technology of China ; Ministry of Health of China ; National Natural Science Foundation of China ; National Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/44187]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心
通讯作者Xie, Jiaheng
作者单位1.Univ Delaware, Lerner Coll Business & Econ, Dept Accounting & MIS, Newark, DE USA
2.Shenzhen Artificial Intelligence & Data Sci Res I, Shenzhen, Guangdong, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Arizona State Univ, Dept Informat Syst, Tempe, AZ USA
5.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Xie, Jiaheng,Zhang, Zhu,Liu, Xiao,et al. Unveiling the Hidden Truth of Drug Addiction: A Social Media Approach Using Similarity Network-Based Deep Learning[J]. JOURNAL OF MANAGEMENT INFORMATION SYSTEMS,2021,38(1):166-195.
APA Xie, Jiaheng,Zhang, Zhu,Liu, Xiao,&Zeng, Daniel.(2021).Unveiling the Hidden Truth of Drug Addiction: A Social Media Approach Using Similarity Network-Based Deep Learning.JOURNAL OF MANAGEMENT INFORMATION SYSTEMS,38(1),166-195.
MLA Xie, Jiaheng,et al."Unveiling the Hidden Truth of Drug Addiction: A Social Media Approach Using Similarity Network-Based Deep Learning".JOURNAL OF MANAGEMENT INFORMATION SYSTEMS 38.1(2021):166-195.

入库方式： OAI收割

来源：自动化研究所

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