Sentiment Analysis for Social Media

Moreno, Antonio; Iglesias, Carlos A.

doi:10.3390/books978-3-03928-573-0

dc.contributor.author	Moreno, Antonio	*
dc.contributor.author	Iglesias, Carlos A.	*
dc.date.accessioned	2021-02-12T03:23:14Z
dc.date.available	2021-02-12T03:23:14Z
dc.date.issued	2020	*
dc.date.submitted	2020-06-09 16:38:56	*
dc.identifier	45980	*
dc.identifier.uri	https://directory.doabooks.org/handle/20.500.12854/59238
dc.description.abstract	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.	*
dc.language	English	*
dc.subject	TA1-2040	*
dc.subject	T1-995	*
dc.subject.classification	thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology	en_US
dc.subject.other	opinion mining	*
dc.subject.other	affect computing	*
dc.subject.other	health insurance	*
dc.subject.other	Twitter	*
dc.subject.other	hybrid vectorization	*
dc.subject.other	violence against women	*
dc.subject.other	word association	*
dc.subject.other	collaborative schemes of sentiment analysis and sentiment systems	*
dc.subject.other	random forest	*
dc.subject.other	cyber-aggression	*
dc.subject.other	deep learning	*
dc.subject.other	online review	*
dc.subject.other	emotion analysis	*
dc.subject.other	lexicon construction	*
dc.subject.other	provider networks	*
dc.subject.other	text mining	*
dc.subject.other	sentiment lexicon	*
dc.subject.other	social media	*
dc.subject.other	sentiment-aware word embedding	*
dc.subject.other	psychographic segmentation	*
dc.subject.other	medical web forum	*
dc.subject.other	gender classification	*
dc.subject.other	racism	*
dc.subject.other	sentiment analysis	*
dc.subject.other	sentiment classification	*
dc.subject.other	sentiment word analysis	*
dc.subject.other	social networks	*
dc.subject.other	convolutional neural network	*
dc.subject.other	review data mining	*
dc.subject.other	machine learning	*
dc.subject.other	emotion classification	*
dc.subject.other	big data-driven marketing	*
dc.subject.other	text feature representation	*
dc.subject.other	recommender system	*
dc.subject.other	user preference prediction	*
dc.subject.other	violence based on sexual orientation	*
dc.subject.other	semantic networks	*
dc.title	Sentiment Analysis for Social Media	*
dc.type	book
oapen.identifier.doi	10.3390/books978-3-03928-573-0	*
oapen.relation.isPublishedBy	46cabcaa-dd94-4bfe-87b4-55023c1b36d0	*
oapen.relation.isbn	9783039285730	*
oapen.relation.isbn	9783039285723	*
oapen.pages	152	*
oapen.edition	1st	*

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