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- W2534257000 abstract "In this paper we address a new problem of predicting affect and well-being scales in a real-worldsetting of heterogeneous, longitudinal and non-synchronous textual as well as non-linguistic datathat can be harvested from on-line media and mobile phones. We describe the method for collectingthe heterogeneous longitudinal data, how features are extracted to address missing informationand differences in temporal alignment, and how the latter are combined to yield promisingpredictions of affect and well-being on the basis of widely used psychological scales. We achievea coefficient of determination (R2) of 0.71 − 0.76 and a ρ of 0.68 − 0.87 which is higher thanthe state-of-the art in equivalent multi-modal tasks for affect." @default.
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- W2534257000 date "2016-12-01" @default.
- W2534257000 modified "2023-09-28" @default.
- W2534257000 title "Combining heterogeneous user generated data to sense well-being" @default.
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