A corpus for mining drug-related knowledge from Twitter chatter: Language models and their utilities

In this data article, we present to the data science, natural language processing and public heath communities an unlabeled corpus and a set of language models. We collected the data from Twitter using drug names as keywords, including their common misspelled forms. Using this data, which is rich in...

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Detalles Bibliográficos
Autores principales: Sarker, Abeed, Gonzalez, Graciela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144647/
https://www.ncbi.nlm.nih.gov/pubmed/27981203
http://dx.doi.org/10.1016/j.dib.2016.11.056

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144647/
https://www.ncbi.nlm.nih.gov/pubmed/27981203
http://dx.doi.org/10.1016/j.dib.2016.11.056

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