Inferring Smoking Status from User Generated Content in an Online Cessation Community | Zendy

Michael S. Amato | Zendy; George D. Papandonatos | Zendy; Sarah Cha | Zendy; Xi Wang | Zendy; Kang Zhao | Zendy; Amy M. Cohn | Zendy; Jennifer Pearson | Zendy; Amanda L. Graham | Zendy

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Inferring Smoking Status from User Generated Content in an Online Cessation Community

Author(s) -

Michael S. Amato,

George D. Papandonatos,

Sarah Cha,

Xi Wang,

Kang Zhao,

Amy M. Cohn,

Jennifer Pearson,

Amanda L. Graham

Publication year - 2018

Publication title -

nicotine and tobacco research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.338

H-Index - 113

eISSN - 1469-994X

pISSN - 1462-2203

DOI - 10.1093/ntr/nty014

Subject(s) - smoking cessation , abstinence , concordance , psychological intervention , observational study , medicine , intervention (counseling) , randomized controlled trial , inference , the internet , psychology , computer science , world wide web , psychiatry , artificial intelligence , surgery , pathology

User generated content (UGC) is a valuable but underutilized source of information about individuals who participate in online cessation interventions. This study represents a first effort to passively detect smoking status among members of an online cessation program using UGC.

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