Published on 08.01.18 in Vol 4, No 1 (2018): Jan-Mar
Works citing "Detecting Novel and Emerging Drug Terms Using Natural Language Processing: A Social Media Corpus Study"
According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.7726):
(note that this is only a small subset of citations)
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Lavertu A, Altman RB. RedMed: Extending drug lexicons for social media applications. Journal of Biomedical Informatics 2019;99:103307
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Adams N, Artigiani EE, Wish ED. Choosing Your Platform for Social Media Drug Research and Improving Your Keyword Filter List. Journal of Drug Issues 2019;49(3):477
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Mavragani A, Ochoa G, Tsagarakis KP. Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review. Journal of Medical Internet Research 2018;20(11):e270
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Miliano C, Margiani G, Fattore L, De Luca M. Sales and Advertising Channels of New Psychoactive Substances (NPS): Internet, Social Networks, and Smartphone Apps. Brain Sciences 2018;8(7):123
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Hu H, Phan N, Chun SA, Geller J, Vo H, Ye X, Jin R, Ding K, Kenne D, Dou D. An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning. Computational Social Networks 2019;6(1)
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Mackey T, Kalyanam J, Klugman J, Kuzmenko E, Gupta R. Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access. Journal of Medical Internet Research 2018;20(4):e10029
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Artigiani EE, Wish ED. Introducing the National Drug Early Warning System. Current Opinion in Psychiatry 2020;33(4):319
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Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439
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Li Z, Du X, Liao X, Jiang X, Champagne-Langabeer T. Demystifying the Dark Web Opioid Trade: Content Analysis on Anonymous Market Listings and Forum Posts. Journal of Medical Internet Research 2021;23(2):e24486
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Xie J, Zhang Z, Liu X, Zeng D. Unveiling the Hidden Truth of Drug Addiction: A Social Media Approach Using Similarity Network-Based Deep Learning. Journal of Management Information Systems 2021;38(1):166
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Wiesinger H, Wang Z, Hellweg S. Deep Dive into Plastic Monomers, Additives, and Processing Aids. Environmental Science & Technology 2021;55(13):9339
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Saran SK, Salinas KZ, Foulds J, Kaynak , Hoglen B, Houser KR, Krebs NM, Yingst JM, Allen SI, Bordner CR, Hobkirk AL. A Comparison of Vaping Behavior, Perceptions, and Dependence among Individuals Who Vape Nicotine, Cannabis, or Both. International Journal of Environmental Research and Public Health 2022;19(16):10392
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Fuller A, Vasek M, Mariconti E, Johnson SD. Understanding and preventing the advertisement and sale of illicit drugs to young people through social media: A multidisciplinary scoping review. Drug and Alcohol Review 2024;43(1):56
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Tang LA, Korona-Bailey J, Zaras D, Roberts A, Mukhopadhyay S, Espy S, Walsh CG. Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study. JMIR Public Health and Surveillance 2023;9:e45246
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Yuan Y, Kasson E, Taylor J, Cavazos-Rehg P, De Choudhury M, Aledavood T. Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: A Machine Learning Approach (Preprint). JMIR Formative Research 2023;
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According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.7726):
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González SM, Sakata TC, Nogueira RR. Artificial Intelligence and Soft Computing. 2020. Chapter 21:231
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Lobantsev A, Loginova V, Burlakova Y, Andreev N, Matveeva V, Filimonova I, Dobrenko N, Gusarova N. Digital Transformation and Global Society. 2020. Chapter 35:479
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Vyas P, Vyas G, Chauhan A, Rawat R, Telang S, Gottumukkala M. Using Computational Intelligence for the Dark Web and Illicit Behavior Detection. 2022. chapter 15:272
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