Cargando…
Utilizing deep learning and graph mining to identify drug use on Twitter data
BACKGROUND: The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of a collected set of Twitter data, a model will be developed for predicting positively referenced, drug-related tweets. Fr...
Autores principales: | Tassone, Joseph, Yan, Peizhi, Simpson, Mackenzie, Mendhe, Chetan, Mago, Vijay, Choudhury, Salimur |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772918/ https://www.ncbi.nlm.nih.gov/pubmed/33380324 http://dx.doi.org/10.1186/s12911-020-01335-3 |
Ejemplares similares
-
SURF: identifying and allocating resources during Out-of-Hospital Cardiac Arrest
por: Rao, Gaurav, et al.
Publicado: (2020) -
Identifying health related occupations of Twitter users through word embedding and deep neural networks
por: Zainab, Kazi, et al.
Publicado: (2022) -
21 Recipes for Mining Twitter
por: Russell, Matthew
Publicado: (2011) -
Synergy Between Public and Private Health Care Organizations During COVID-19 on Twitter: Sentiment and Engagement Analysis Using Forecasting Models
por: Singhal, Aditya, et al.
Publicado: (2022) -
A corpus for mining drug-related knowledge from Twitter chatter: Language models and their utilities
por: Sarker, Abeed, et al.
Publicado: (2016)