Explore our sister journals here.

Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Published on 26.09.17 in Vol 3, No 3 (2017): Jul-Sept

This paper is in the following e-collection/theme issue:

Works citing "Classification of Twitter Users Who Tweet About E-Cigarettes"

Annice Kim, Thomas Miano, Robert Chew, Matthew Eggers, James Nonnemaker

JMIR Public Health Surveill 2017 (Sep 26); 3(3):e63 

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.8060):

(note that this is only a small subset of citations)

  1. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  2. Murphy J, Hsieh YP, Wenger M, Kim AE, Chew R. Supplementing a survey with respondent Twitter data to measure e-cigarette information exposure. Information, Communication & Society 2019;22(5):622
    CrossRef
  3. Staal YC, van de Nobelen S, Havermans A, Talhout R. New Tobacco and Tobacco-Related Products: Early Detection of Product Development, Marketing Strategies, and Consumer Interest. JMIR Public Health and Surveillance 2018;4(2):e55
    CrossRef
  4. Albalawi Y, Nikolov NS, Buckley J. Trustworthy Health-Related Tweets on Social Media in Saudi Arabia: Tweet Metadata Analysis. Journal of Medical Internet Research 2019;21(10):e14731
    CrossRef
  5. Tassone J, Yan P, Simpson M, Mendhe C, Mago V, Choudhury S. Utilizing deep learning and graph mining to identify drug use on Twitter data. BMC Medical Informatics and Decision Making 2020;20(S11)
    CrossRef
  6. Ho RC, Withanage MS, Khong KW. Sentiment drivers of hotel customers: a hybrid approach using unstructured data from online reviews. Asia-Pacific Journal of Business Administration 2020;12(3/4):237
    CrossRef
  7. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660
    CrossRef
  8. Gao Y, Xie Z, Li D. Electronic Cigarette Users' Perspective on the COVID-19 Pandemic: Observational Study Using Twitter Data. JMIR Public Health and Surveillance 2021;7(1):e24859
    CrossRef
  9. Robertson L, Joshi A, Legg T, Wellock G, Ray K, Evans-Reeves K. Exploring the Twitter activity around the eighth meeting of the Conference of the Parties to the WHO Framework Convention on Tobacco Control. Tobacco Control 2022;31(1):50
    CrossRef
  10. Cochran C, Robertson L, Hoek J. Online marketing activity following New Zealand’s vaping legislation. Tobacco Control 2023;32(2):263
    CrossRef
  11. Bardier C, Yang JS, Li J, Mackey TK. Characterizing alternative and emerging tobacco product transition of use behavior on Twitter. BMC Research Notes 2021;14(1)
    CrossRef
  12. Alhayan F, Pennington D, Ayouni S. Twitter use by the dementia community during COVID-19: a user classification and social network analysis. Online Information Review 2023;47(1):41
    CrossRef
  13. Benítez-Andrades JA, Alija-Pérez J, Vidal M, Pastor-Vargas R, García-Ordás MT. Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)–Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study. JMIR Medical Informatics 2022;10(2):e34492
    CrossRef
  14. Ezike NC, Ames Boykin A, Dobbs PD, Mai H, Primack BA. Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series. JMIR Infodemiology 2022;2(2):e37412
    CrossRef
  15. Lanza-Cruz I, Berlanga R, Aramburu MJ. Multidimensional Author Profiling for Social Business Intelligence. Information Systems Frontiers 2024;26(1):195
    CrossRef
  16. . Power Dynamics and Corporate Power in Governance Processes: Evidence From U.S. Environmental Governance Systems. The American Review of Public Administration 2022;52(3):206
    CrossRef
  17. Pilipiec P, Liwicki M, Bota A. Using Machine Learning for Pharmacovigilance: A Systematic Review. Pharmaceutics 2022;14(2):266
    CrossRef
  18. Yan Y, Chen C, Liu Y, Zhang Z, Xu L, Pu K. Application of Machine Learning for the Prediction of Etiological Types of Classic Fever of Unknown Origin. Frontiers in Public Health 2021;9
    CrossRef
  19. Ma S, Kaareen A, Park H, He Y, Jiang S, Qiu Z, Xie Z, Li D, Chen J, O’Connor RJ, Fong GT, Shang C. How to Identify e-Cigarette Brands Available in the United States During 2020-2022: Development and Usability Study. JMIR Formative Research 2024;8:e47570
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.8060):

  1. Daouadi KE, Zghal Rebaï R, Amous I. Machine Learning for Networking. 2019. Chapter 3:33
    CrossRef
  2. Martinez LS, Tsou M, Spitzberg BH. Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics. 2021. Chapter 11:203
    CrossRef