Titlebook: Emotion Detection in Natural Language Processing; Federica Cavicchio Book 2025 The Editor(s) (if applicable) and The Author(s), under excl

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Synthesis Lectures on Human Language Technologieshttp://image.papertrans.cn/f/image/320575.jpg

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https://doi.org/10.1007/0-387-35098-5xperiences such as affect, feelings, sentiment, and opinions. It highlights various models of emotion classification, specifically distinguishing between categorical and dimensional approaches. Categorical models of emotion classify emotions into distinct categories: happiness, sadness, anger, fear,

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Molecular Mechanisms of Dementiarvised learning identifies complex emotional patterns without needing predefined datasets and labelled data. This approach is contrasted with supervised learning methods, which rely on annotated datasets to train models, enabling emotion detection based on specific criteria. We also introduce word e

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