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Journal of Health Communication
International Perspectives
Volume 25, 2020 - Issue 3
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Original Article

Linguistic Predictors of Problematic Drinking in Alcohol-related Facebook Posts

Lyn M. van SwolDepartment of Communication Arts, University of Wisconsin–Madison, Madison, USACorrespondence[email protected]
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,
Chen-Ting ChangDepartment of Communication Arts, University of Wisconsin–Madison, Madison, USAView further author information
,
Bradley KerrDepartment of Pediatrics, University of Wisconsin–Madison, Madison, USAView further author information
&
Megan MorenoDepartment of Pediatrics, University of Wisconsin–Madison, Madison, USAView further author information
Pages 214-222 | Published online: 25 Feb 2020

Citations (5)

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Read on this site (1)

Femke Geusens, Y. Anthony Chen, Bradley Kerr & Megan Moreno. (2023) Disentangling Between-Person Level From Within-Person Level Relationships: How Sharing Alcohol References on Facebook and Alcohol Use Are Associated Over Time. Media Psychology 26:3, pages 252-277.
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Articles from other publishers (4)

Caitlin Ferreira, Jeandri Robertson, Raeesah Chohan, Leyland Pitt & Tim Foster. (2023) The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis. Journal of Service Theory and Practice 33:2, pages 309-327.
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Rupa Jose, Matthew Matero, Garrick Sherman, Brenda Curtis, Salvatore Giorgi, Hansen Andrew Schwartz & Lyle H. Ungar. (2022) Using Facebook language to predict and describe excessive alcohol use. Alcoholism: Clinical and Experimental Research 46:5, pages 836-847.
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Mengke Hu, Ryzen Benson, Annie T. Chen, Shu-Hong Zhu & Mike Conway. (2021) Determining the prevalence of cannabis, tobacco, and vaping device mentions in online communities using natural language processing. Drug and Alcohol Dependence 228, pages 109016.
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Benjamin Joseph Ricard & Saeed Hassanpour. (2021) Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes. Journal of Medical Internet Research 23:9, pages e27314.
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