Reprint
Sentiment Analysis for Social Media
Edited by
April 2020
152 pages
- ISBN978-3-03928-572-3 (Paperback)
- ISBN978-3-03928-573-0 (PDF)
This book is a reprint of the Special Issue Sentiment Analysis for Social Media that was published in
Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
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.
Format
- Paperback
License
© 2020 by the authors; CC BY-NC-ND license
Keywords
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; cyber-aggression; sentiment analysis; random forest; racism; violence based on sexual orientation; violence against women; social networks; psychographic segmentation; user preference prediction; lexicon construction; online review; recommender system; big data-driven marketing; social media; Twitter; text mining; sentiment analysis; word association; health insurance; provider networks; deep learning; convolutional neural network; sentiment classification; collaborative schemes of sentiment analysis and sentiment systems; review data mining; semantic networks; sentiment word analysis; sentiment analysis; emotion analysis; social media; affect computing