title: TEXT CLASSIFICATION FOR AUTOMATIC DETECTION OF E-CIGARETTE USE AND USE FOR SMOKING CESSATION FROM TWITTER: A FEASIBILITY PILOT.
abstract: Rapid increases in e-cigarette use and potential exposure to harmful byproducts have shifted public health focus to e-cigarettes as a possible drug of abuse. Effective surveillance of use and prevalence would allow appropriate regulatory responses. An ideal surveillance system would collect usage data in real time, focus on populations of interest, include populations unable to take the survey, allow a breadth of questions to answer, and enable geo-location analysis. Social media streams may provide this ideal system. To realize this use case, a foundational question is whether we can detect e-cigarette use at all. This work reports two pilot tasks using text classification to identify automatically Tweets that indicate e-cigarette use and/or e-cigarette use for smoking cessation. We build and define both datasets and compare performance of 4 state of the art classifiers and a keyword search for each task. Our results demonstrate excellent classifier performance of up to 0.90 and 0.94 area under the curve in each category. These promising initial results form the foundation for further studies to realize the ideal surveillance solution.
authors.affiliation: NYU Langone Medical Center, New York, NY 10016, USA, yin.a@nyumc.org.
authors.forename: Yin
authors.initials: Y
authors.lastname: Aphinyanaphongs
authors.forename: Armine
authors.initials: A
authors.lastname: Lulejian
authors.forename: Duncan Penfold
authors.initials: DP
authors.lastname: Brown
authors.forename: Richard
authors.initials: R
authors.lastname: Bonneau
authors.forename: Paul
authors.initials: P
authors.lastname: Krebs
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D066300:Electronic Nicotine Delivery Systems / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D006801:Humans; D016015:Logistic Models; D010865:Pilot Projects; D016540:Smoking Cessation / Q000379:methods* / Q000706:statistics & numerical data; D061108:Social Media / Q000706:statistics & numerical data*; D060388:Support Vector Machine