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- W2892118011 abstract "Detecting fine-grained emotions in online health communities provides insightful information about patients’ emotional states. However, current computational approaches to emotion detection from health-related posts focus only on identifying messages that contain emotions, with no emphasis on the emotion type, using a set of handcrafted features. In this paper, we take a step further and propose to detect fine-grained emotion types from health-related posts and show how high-level and abstract features derived from deep neural networks combined with lexicon-based features can be employed to detect emotions." @default.
- W2892118011 created "2018-09-27" @default.
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- W2892118011 date "2018-01-01" @default.
- W2892118011 modified "2023-10-17" @default.
- W2892118011 title "Fine-Grained Emotion Detection in Health-Related Online Posts" @default.
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- W2892118011 doi "https://doi.org/10.18653/v1/d18-1147" @default.
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