2016 IEEE Symposium on Technologies for Homeland Security (HST) 2016
DOI: 10.1109/ths.2016.7568888
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Feedback-based social media filtering tool for improved situational awareness

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Cited by 3 publications
(5 citation statements)
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“…Assim sendo, será sempre imprescindível filtrar as informações que são publicadas e compartilhadas nas mídias, durante a ocorrência de desastres ou emergências, a fim de identificar erros, eliminar notícias falsas e, ainda, suprimir termos ou palavras que possam causar confusão à população em risco (Thornton;Deangelus;Miller, 2016).…”
Section: Latin Americanunclassified
“…Assim sendo, será sempre imprescindível filtrar as informações que são publicadas e compartilhadas nas mídias, durante a ocorrência de desastres ou emergências, a fim de identificar erros, eliminar notícias falsas e, ainda, suprimir termos ou palavras que possam causar confusão à população em risco (Thornton;Deangelus;Miller, 2016).…”
Section: Latin Americanunclassified
“…[ 5 , [19] , [20] , [21] , [22] ]. Only a few papers like [ 4 , [23] , [24] , [25] ] are independent of a specific disease. Most literature on this field relies on information extraction from text, while only a few works like [ 25 ] also integrate information extraction from images.…”
Section: Literature Review and Research Gapmentioning
confidence: 99%
“…Only a few papers like [ 4 , [23] , [24] , [25] ] are independent of a specific disease. Most literature on this field relies on information extraction from text, while only a few works like [ 25 ] also integrate information extraction from images. Additionally, a majority of literature incorporates microblogging platforms like Twitter, e.g., [ 3 , 4 , 9 , 26 , 27 ], and Sina Weibo [ 21 , 28 , 29 ].…”
Section: Literature Review and Research Gapmentioning
confidence: 99%
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