LEADER 02915nam 2200745z- 450 001 9910404092303321 005 20231214133105.0 010 $a3-03928-573-4 035 $a(CKB)4100000011302215 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/59238 035 $a(EXLCZ)994100000011302215 100 $a20202102d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSentiment Analysis for Social Media 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (152 p.) 311 $a3-03928-572-6 330 $aSentiment 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. 610 $aopinion mining 610 $aaffect computing 610 $ahealth insurance 610 $aTwitter 610 $ahybrid vectorization 610 $aviolence against women 610 $aword association 610 $acollaborative schemes of sentiment analysis and sentiment systems 610 $arandom forest 610 $acyber-aggression 610 $adeep learning 610 $aonline review 610 $aemotion analysis 610 $alexicon construction 610 $aprovider networks 610 $atext mining 610 $asentiment lexicon 610 $asocial media 610 $asentiment-aware word embedding 610 $apsychographic segmentation 610 $amedical web forum 610 $agender classification 610 $aracism 610 $asentiment analysis 610 $asentiment classification 610 $asentiment word analysis 610 $asocial networks 610 $aconvolutional neural network 610 $areview data mining 610 $amachine learning 610 $aemotion classification 610 $abig data-driven marketing 610 $atext feature representation 610 $arecommender system 610 $auser preference prediction 610 $aviolence based on sexual orientation 610 $asemantic networks 700 $aMoreno$b Antonio$4auth$0419397 702 $aIglesias$b Carlos A$4auth 906 $aBOOK 912 $a9910404092303321 996 $aSentiment Analysis for Social Media$93020240 997 $aUNINA