Modeling Spatiotemporal Factors Associated With Sentiment on Twitter: Synthesis and Suggestions for Improving the Identification of Localized Deviations

BACKGROUND: Studies examining how sentiment on social media varies depending on timing and location appear to produce inconsistent results, making it hard to design systems that use sentiment to detect localized events for public health applications. OBJECTIVE: The aim of this study was to measure h...

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Detalles Bibliográficos
Autores principales: Shah, Zubair, Martin, Paige, Coiera, Enrico, Mandl, Kenneth D, Dunn, Adam G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682275/
https://www.ncbi.nlm.nih.gov/pubmed/31344669
http://dx.doi.org/10.2196/12881

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682275/
https://www.ncbi.nlm.nih.gov/pubmed/31344669
http://dx.doi.org/10.2196/12881

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