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Sentiment Analysis for Social Media
Carlos A. Iglesias and Antonio Moreno
2020
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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.
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Keywords
- affect computing
- big data-driven marketing
- collaborative schemes of sentiment analysis and sentiment systems
- convolutional neural network
- cyber-aggression
- deep learning
- emotion analysis
- emotion classification
- gender classification
- Health Insurance
- hybrid vectorization
- lexicon construction
- Machine learning
- medical web forum
- online review
- opinion mining
- provider networks
- psychographic segmentation
- Racism
- random forest
- recommender system
- review data mining
- semantic networks
- sentiment analysis
- sentiment classification
- sentiment lexicon
- sentiment word analysis
- sentiment-aware word embedding
- Social media
- Social networks
- text feature representation
- Text Mining
- user preference prediction
- Violence against women
- violence based on sexual orientation
- word association
Links
DOI: 10.3390/books978-3-03928-573-0Editions
