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- W4286851502 abstract "This paper presents a predictive model for Influenza-Like-Illness, based on Twitter traffic. We gather data from Twitter based on a set of keywords used in the Influenza wikipedia page, and perform feature selection over all words used in 3 years worth of tweets, using real ILI data from the Greek CDC. We select a small set of words with high correlation to the ILI score, and train a regression model to predict the ILI score cases from the word features. We deploy this model on a streaming application and feed the resulting time-series to FluHMM, an existing prediction model for the phases of the epidemic. We find that Twitter traffic offers a good source of information and can generate early warnings compared to the existing sentinel protocol using a set of associated physicians all over Greece." @default.
- W4286851502 created "2022-07-25" @default.
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- W4286851502 date "2021-11-20" @default.
- W4286851502 modified "2023-10-05" @default.
- W4286851502 title "Detecting Influenza Epidemics on Twitter" @default.
- W4286851502 doi "https://doi.org/10.48550/arxiv.2111.10675" @default.
- W4286851502 hasPublicationYear "2021" @default.
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