Sentiment Analysis for Social Media
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Beschreibung
Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.
Autor*in
Carlos A. Iglesias
Themen in »Sentiment Analysis for Social Media«
opinion mining sentiment analysis emotion classification deep learning Twitter sentiment analysis gender classification machine learning deep learning medical web forum emotion classification sentiment lexicon text feature representation hybrid vectorization sentiment-aware word embedding