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Sentiment Analysis for Social Media

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 indus...

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Bibliographic Details
Main Author: Moreno, Antonio
Other Authors: Iglesias, Carlos A.
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
Machine Learning
Semantic Networks
Psychographic Segmentation
Violence Against Women
Random Forest
Big Data-driven Marketing
Emotion Classification
Online Review
Deep Learning
History Of Engineering And Technology / Bicssc
Social Media
Collaborative Schemes Of Sentiment Analysis And Sentiment Systems
Affect Computing
User Preference Prediction
Provider Networks
Racism
Text Mining
Review Data Mining
Sentiment Word Analysis
Health Insurance
Word Association
Social Networks
Sentiment Lexicon
Sentiment Analysis
Violence Based On Sexual Orientation
Text Feature Representation
Cyber-aggression
Medical Web Forum
Twitter
Gender Classification
Lexicon Construction
Opinion Mining
Sentiment Classification
Hybrid Vectorization
Convolutional Neural Network
Emotion Analysis
Recommender System
Sentiment-aware Word Embedding
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
Physical Description:1 electronic resource (152 p.)
ISBN:9783039285730
9783039285723
books978-3-03928-573-0

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