15 research outputs found

    ILI nowcasting results (current week) for six geolocations estimated using cross-validation over four years (2011–2014).

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    <p>Models: AdaBoost, SVM with a linear kernel, and LSTM. Metrics: Pearson correlation (CORR), RMSPE (%), MAPE (%), and RMSE. The highest performance results within each datatype are highlighted in bold.</p

    Tweet distribution across geolocations.

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    <p>The number of tweets collected within a 25-mile radius of military installations for 31 geolocations.</p

    Location-specific ILI dynamics.

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    <p>Weekly ILI proportions between 2011 and 2014 for six example geolocations.</p

    True vs. predicted ILI proportions (real-time current week estimates) as a function of time (2011–2014) for six geolocations.

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    <p>We plot true ILI proportions (True), predictions from social media (tweet and network) features (SM), and predictions from ILI historical data (ILI) obtained using LSTM model.</p

    True vs. predicted ILI dynamics one week in advance as a function of time in 2014 for 31 geolocations.

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    <p>We plot true ILI values (True), one week forecasts obtained using social media features only (SM), ILI historical data (ILI), and combined ILI + SM data (ILISM).</p

    ILI nowcasting results for six geolocations obtained using SMOnly model trained on nine types of social media signals.

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    <p>We contrast Pearson and RMSE for six geolocations. Locations with labels show the best (embeddings, unigrams, hashtags and mentions), on the right from the dotted vertical line, and the worst (stylistic and topics) social media signals.</p
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