An NLP task where models classify text by emotional tone or opinion polarity, commonly used for analyzing customer reviews, social media, and brand perception.
Teaching AI to understand feelings — like figuring out if a movie review is happy or angry.
When AI reads text and determines if the mood is positive, negative, or neutral — useful for analyzing reviews, social media, and customer feedback.
An NLP task where models classify text by emotional tone or opinion polarity, commonly used for analyzing customer reviews, social media, and brand perception.
The computational identification of subjective information in text — classifying opinion polarity, detecting emotion categories, and extracting aspect-level sentiment from unstructured data.
Opinion mining via supervised or zero-shot classification over affect dimensions — encompassing document-level polarity, aspect-based sentiment extraction, and fine-grained emotion detection, with domain adaptation challenges in sarcasm, irony, and implicit sentiment.
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