LEADER 05556nam 22007815 450 001 9910253909103321 005 20200706080937.0 010 $a3-319-55394-1 024 7 $a10.1007/978-3-319-55394-8 035 $a(CKB)3710000001152014 035 $a(DE-He213)978-3-319-55394-8 035 $a(MiAaPQ)EBC4840135 035 $a(PPN)200513885 035 $a(EXLCZ)993710000001152014 100 $a20170411d2017 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA Practical Guide to Sentiment Analysis /$fedited by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (VII, 196 p. 16 illus., 7 illus. in color.) 225 1 $aSocio-Affective Computing,$x2509-5706 ;$v5 311 $a3-319-55392-5 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aPreface -- Affective Computing and Sentiment Analysis -- Many Facets of Sentiment Analysis -- Reflections on Sentiment/Opinion Analysis -- Challenges in Sentiment Analysis --  Sentiment Resources: Lexicons and Datasets -- Generative Models for Sentiment Analysis and Opinion Mining -- Social Media Summarization -- Deception Detection and Opinion Spam -- Concept-Level Sentiment Analysis with SenticNet -- Index. 330 $aThis edited work presents studies and discussions that clarify the challenges and opportunities of sentiment analysis research. While sentiment analysis research has become very popular in the past ten years, most companies and researchers still approach it simply as a polarity detection problem. In reality, sentiment analysis is a ?suitcase problem? that requires tackling many natural language processing subtasks, including microtext analysis, sarcasm detection, anaphora resolution, subjectivity detection and aspect extraction.   In this book, the authors propose an overview of the main issues and challenges associated with current sentiment analysis research and provide some insights on practical tools and techniques that can be exploited to both advance the state of the art in all sentiment analysis subtasks and explore new areas in the same context. Readers will discover sentiment mining techniques that can be exploited for the creation and automated upkeep of review and opinion aggregation websites, in which opinionated text and videos are continuously gathered from the Web and not restricted to just product reviews, but also to wider topics such as political issues and brand perception. The book also enables researchers to see how affective computing and sentiment analysis have a great potential as a sub-component technology for other systems. They can enhance the capabilities of customer relationship management and recommendation systems allowing, for example, to find out which features customers are particularly happy about or to exclude from the recommendations items that have received very negative feedbacks. Similarly, they can be exploited for affective tutoring and affective entertainment or for troll filtering and spam detection in online social communication. 410 0$aSocio-Affective Computing,$x2509-5706 ;$v5 606 $aMedicine 606 $aInformation storage and retrieval 606 $aApplied linguistics 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aUser interfaces (Computer systems) 606 $aStatistics 606 $aBiomedicine, general$3https://scigraph.springernature.com/ontologies/product-market-codes/B0000X 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aApplied Linguistics$3https://scigraph.springernature.com/ontologies/product-market-codes/N13000 606 $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006 606 $aUser Interfaces and Human Computer Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/I18067 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 615 0$aMedicine. 615 0$aInformation storage and retrieval. 615 0$aApplied linguistics. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 0$aUser interfaces (Computer systems) 615 0$aStatistics. 615 14$aBiomedicine, general. 615 24$aInformation Storage and Retrieval. 615 24$aApplied Linguistics. 615 24$aMathematical and Computational Engineering. 615 24$aUser Interfaces and Human Computer Interaction. 615 24$aStatistics and Computing/Statistics Programs. 676 $a006.35 702 $aCambria$b Erik$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDas$b Dipankar$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBandyopadhyay$b Sivaji$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFeraco$b Antonio$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910253909103321 996 $aPractical Guide to Sentiment Analysis$94215506 997 $aUNINA