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Whose Post Is It? Predicting E-cigarette Brand from Social Media Posts.
Vandewater, Elizabeth A; Clendennen, Stephanie L; Hébert, Emily T; Bigman, Galya; Jackson, Christian D; Wilkinson, Anna V; Perry, Cheryl L.
Afiliación
  • Vandewater EA; Director of Data Science and Research Services, The University of Texas at Austin, Population Research Center, Austin, TX.
  • Clendennen SL; Predoctoral Fellow, UTHealth School of Public Health in Austin, TX.
  • Hébert ET; Postdoctoral Research Fellow, The University of Oklahoma Health Sciences Center, Oklahoma City, OK.
  • Bigman G; Graduate Research Assistant, UTHealth School of Public Health in Austin, TX.
  • Jackson CD; Statistician, UTHealth School of Public Health in Austin, TX.
  • Wilkinson AV; Associate Professor, UTHealth School of Public Health in Austin, TX.
  • Perry CL; Professor and Regional Dean, UTHealth School of Public Health in Austin, TX.
Tob Regul Sci ; 4(2): 30-43, 2018 Mar.
Article en En | MEDLINE | ID: mdl-30662930
ABSTRACT

OBJECTIVES:

E-cigarette advertisers know that 76% of youth use social media, yet little is known about the nature of e-cigarette advertising on social media most favored by youth. We utilized text-mining to characterize e-cigarette advertising and marketing messages from image-focused social media brand sites, and to construct and test an algorithm for predicting brand from brand-generated social media posts.

METHODS:

Data comprised 5022 unique posts accompanied by an image from Facebook, Instagram or Pinterest e-cigarette brand pages for Blu, Logic, Metro, and NJOY from February 2012 to April 2015. Text-tokenization was used to quantify text for use as predictors in analyses.

RESULTS:

Blu had the largest social media presence (65%), followed by Logic (16%), NJOY (12%) and Metro (7%). Blu's average post length was significantly shorter than all other brands. Words most commonly used in posts differed by brand. Regression analyses successfully differentiated Blu and NJOY brands from other brands.

CONCLUSIONS:

Analyses revealed e-cigarette brands used different types of messages to appeal to social media users. Whereas words used by Blu and NJOY sold a "lifestyle," words used by Logic and Metro relied on device and product identification.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Tob Regul Sci Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Tob Regul Sci Año: 2018 Tipo del documento: Article