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

Infodemiology and Infoveillance (1349) Substance Abuse (419) Machine Learning (1465) Alcohol Abuse, Alcoholism Prevention and Recovery (300) Mass Media/Social Media Communication and Campaigns (461) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Natural Language Processing (693) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Methods and New Tools in Mental Health Research (454)

Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27314, first published .
Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes

Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes

Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes

Authors of this article:

Benjamin Joseph Ricard1 Author Orcid Image ;   Saeed Hassanpour1, 2, 3 Author Orcid Image
Article Authors Cited by (9) Tweetations (15) Metrics

Journals

  1. Ang C, Venkatachala R. Generalizability of Machine Learning to Categorize Various Mental Illness Using Social Media Activity Patterns. Societies 2023;13(5):117 View
  2. Chi Y, Chen H. Investigating Substance Use via Reddit: Systematic Scoping Review. Journal of Medical Internet Research 2023;25:e48905 View
  3. King A, Dunbar N, Margolin D, Chunara R, Tong C, Jih-Vieira L, Matsen C, Niederdeppe J. Global prevalence and content of information about alcohol use as a cancer risk factor on Twitter. Preventive Medicine 2023;177:107728 View
  4. Carabot F, Donat-Vargas C, Santoma-Vilaclara J, Ortega M, García-Montero C, Fraile-Martínez O, Zaragoza C, Monserrat J, Alvarez-Mon M, Alvarez-Mon M. Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study. Journal of Medical Internet Research 2023;25:e45660 View
  5. Chart-Pascual J, Montero-Torres M, Ortega M, Mar-Barrutia L, Zorrilla Martinez I, Alvarez-Mon M, Gonzalez-Pinto A, Alvarez-Mon M. Areas of interest and sentiment analysis towards second generation antipsychotics, lithium and mood stabilizing anticonvulsants: Unsupervised analysis using Twitter. Journal of Affective Disorders 2024;351:649 View

Books/Policy Documents

  1. Poorni R, Madhavan P. Computational Intelligence in Data Science. View
  2. Alen G, Riordan B, Anderson-Luxford D, Kuntsche E. New Directions in Addiction Science. View