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Sentiment Analysis for Social Media

dc.contributor.authorMoreno, Antonio*
dc.contributor.authorIglesias, Carlos A.*
dc.date.accessioned2021-02-12T03:23:14Z
dc.date.available2021-02-12T03:23:14Z
dc.date.issued2020*
dc.date.submitted2020-06-09 16:38:56*
dc.identifier45980*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/59238
dc.description.abstractSentiment 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.languageEnglish*
dc.subjectTA1-2040*
dc.subjectT1-995*
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technologyen_US
dc.subject.otheropinion mining*
dc.subject.otheraffect computing*
dc.subject.otherhealth insurance*
dc.subject.otherTwitter*
dc.subject.otherhybrid vectorization*
dc.subject.otherviolence against women*
dc.subject.otherword association*
dc.subject.othercollaborative schemes of sentiment analysis and sentiment systems*
dc.subject.otherrandom forest*
dc.subject.othercyber-aggression*
dc.subject.otherdeep learning*
dc.subject.otheronline review*
dc.subject.otheremotion analysis*
dc.subject.otherlexicon construction*
dc.subject.otherprovider networks*
dc.subject.othertext mining*
dc.subject.othersentiment lexicon*
dc.subject.othersocial media*
dc.subject.othersentiment-aware word embedding*
dc.subject.otherpsychographic segmentation*
dc.subject.othermedical web forum*
dc.subject.othergender classification*
dc.subject.otherracism*
dc.subject.othersentiment analysis*
dc.subject.othersentiment classification*
dc.subject.othersentiment word analysis*
dc.subject.othersocial networks*
dc.subject.otherconvolutional neural network*
dc.subject.otherreview data mining*
dc.subject.othermachine learning*
dc.subject.otheremotion classification*
dc.subject.otherbig data-driven marketing*
dc.subject.othertext feature representation*
dc.subject.otherrecommender system*
dc.subject.otheruser preference prediction*
dc.subject.otherviolence based on sexual orientation*
dc.subject.othersemantic networks*
dc.titleSentiment Analysis for Social Media*
dc.typebook
oapen.identifier.doi10.3390/books978-3-03928-573-0*
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0*
oapen.relation.isbn9783039285730*
oapen.relation.isbn9783039285723*
oapen.pages152*
oapen.edition1st*


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