Using Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation

scientific article published on 11 April 2019

Using Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation is …
instance of (P31):
scholarly articleQ13442814

External links are
P8978DBLP publication IDjournals/sensors/Hernandez-Suarez19
P356DOI10.3390/S19071746
P932PMC publication ID6484392
P698PubMed publication ID30979067

P50authorHector Perez-MeanaQ61336471
Aldo Hernandez-SuarezQ88518829
Luis Javier García VillalbaQ52610420
P2093author name stringLuis Javier García Villalba
Gabriel Sanchez-Perez
Karina Toscano-Medina
Aldo Hernandez-Suarez
P2860cites workMatplotlib: A 2D Graphics EnvironmentQ17278583
Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social MediaQ58398430
Long short-term memoryQ24805158
Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ₁ Regularization.Q55315019
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue7
P407language of work or nameEnglishQ1860
P921main subjectXQ918
natural disasterQ8065
word embeddingQ18395344
Word2vecQ22673982
address geocodingQ1346408
recurrent neural networkQ1457734
GeoparsingQ5535557
P304page(s)1746
P577publication date2019-04-11
P1433published inSensorsQ3478643
P1476titleUsing Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation
P478volume19

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