LEADER 03048nam 2200781z- 450 001 9910404092303321 005 20210212 010 $a3-03928-573-4 035 $a(CKB)4100000011302215 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/59238 035 $a(oapen)doab59238 035 $a(EXLCZ)994100000011302215 100 $a20202102d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSentiment Analysis for Social Media 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (152 p.) 311 08$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. 606 $aHistory of engineering and technology$2bicssc 610 $aaffect computing 610 $abig data-driven marketing 610 $acollaborative schemes of sentiment analysis and sentiment systems 610 $aconvolutional neural network 610 $acyber-aggression 610 $adeep learning 610 $aemotion analysis 610 $aemotion classification 610 $agender classification 610 $ahealth insurance 610 $ahybrid vectorization 610 $alexicon construction 610 $amachine learning 610 $amedical web forum 610 $aonline review 610 $aopinion mining 610 $aprovider networks 610 $apsychographic segmentation 610 $aracism 610 $arandom forest 610 $arecommender system 610 $areview data mining 610 $asemantic networks 610 $asentiment analysis 610 $asentiment classification 610 $asentiment lexicon 610 $asentiment word analysis 610 $asentiment-aware word embedding 610 $asocial media 610 $asocial networks 610 $atext feature representation 610 $atext mining 610 $aTwitter 610 $auser preference prediction 610 $aviolence against women 610 $aviolence based on sexual orientation 610 $aword association 615 7$aHistory of engineering and technology 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 LEADER 02292oas 2200925 a 450 001 9910303538503321 005 20250921213016.0 011 $a1573-3386 035 $a(DE-599)ZDB2015556-6 035 $a(DE-599)2015556-6 035 $a(OCoLC)44513445 035 $a(CONSER) 2013242222 035 $a(CKB)954925522711 035 $a(EXLCZ)99954925522711 100 $a20000630a19779999 sy 101 0 $aeng 135 $aurmnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGroup 210 $a[New York, N.Y.] $cKluwer Academic-Plenum-Human Sciences Press 311 08$a0362-4021 606 $aGroup psychotherapy$vPeriodicals 606 $aPsychotherapy, Group 606 $aPsychothe?rapie de groupe$vPe?riodiques 606 $aPsychoterapia grupowa$2dbn 606 $aGroup psychotherapy$2fast$3(OCoLC)fst00948490 606 $aGroepspsychotherapie$2gtt 606 $aPsicoterąpia de grup$2thub 608 $aPeriodical. 608 $aCzasopismo psychologiczne.$2dbn 608 $aPeriodicals.$2fast 608 $aPeriodicals.$2lcgft 608 $aRevistes electrņniques.$2thub 615 0$aGroup psychotherapy 615 2$aPsychotherapy, Group. 615 6$aPsychothe?rapie de groupe 615 7$aPsychoterapia grupowa. 615 7$aGroup psychotherapy. 615 17$aGroepspsychotherapie. 615 7$aPsicoterąpia de grup. 676 $a616.8915 712 02$aEastern Group Psychotherapy Society 801 0$bF#A 801 1$bF#A 801 2$bOCLCQ 801 2$bOH1 801 2$bMUQ 801 2$bOCLCQ 801 2$bOCLCS 801 2$bSYB 801 2$bOCLCQ 801 2$bMYG 801 2$bOCLCE 801 2$bOCLCF 801 2$bOCLCO 801 2$bOCLCQ 801 2$bOCLCO 801 2$bOCLCQ 801 2$bUAB 801 2$bOCLCQ 801 2$bAU@ 801 2$bOCLCO 801 2$bWYU 801 2$bUKMGB 801 2$bSFB 801 2$bEQF 801 2$bOCLCQ 801 2$bOCLCO 801 2$bCNMTR 801 2$bQGK 801 2$bAUD 801 2$bOCLCL 801 2$bSXB 801 2$bOCLCL 906 $aJOURNAL 912 $a9910303538503321 996 $aGroup$91917117 997 $aUNINA