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- W2769687515 abstract "We built a personalized system that can predict the upcoming user mood even in days without text-type tweets. We, first, study the correlation of three types of features (cyber, social and physical) with a user mood. Then, we use these features to train a predictive system. The results suggest a statistically significant correlation between user mood and his cyber, social and physical activities distributed among different OSNs, which lead to a low RMSE in our predictive system compared to linguistic-based systems when non-text content is available." @default.
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- W2769687515 date "2017-07-31" @default.
- W2769687515 modified "2023-09-27" @default.
- W2769687515 title "Personalized Mood Prediction Over Online Social Networks" @default.
- W2769687515 cites W1963486426 @default.
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- W2769687515 doi "https://doi.org/10.1145/3110025.3110131" @default.
- W2769687515 hasPublicationYear "2017" @default.
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