Identifying Sentiment of Hookah-Related Posts on Twitter.

Allem, Jon-Patrick; Ramanujam, Jagannathan; Lerman, Kristina; Chu, Kar-Hai; Boley Cruz, Tess; Unger, Jennifer B

Allem, Jon-Patrick; Ramanujam, Jagannathan; Lerman, Kristina; Chu, Kar-Hai; Boley Cruz, Tess; Unger, Jennifer B.

Afiliación

Allem JP; Keck School of Medicine of USC, Los Angeles, CA, United States.
Ramanujam J; Keck School of Medicine of USC, Los Angeles, CA, United States.
Lerman K; University of Southern California, Los Angeles, CA, United States.
Chu KH; University of Pittsburgh, Pittsburgh, PA, United States.
Boley Cruz T; Keck School of Medicine of USC, Los Angeles, CA, United States.
Unger JB; Keck School of Medicine of USC, Los Angeles, CA, United States.

JMIR Public Health Surveill ; 3(4): e74, 2017 Oct 18.

Article en En | MEDLINE | ID: mdl-29046267

Palabras clave

Twitter; big data; bots; hookah; sentiment; social media; waterpipe

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JMIR Public Health Surveill Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google