LEADER 04510nam 22008173 450 001 996464443103316 005 20231110233502.0 010 $a981-16-2881-5 035 $a(CKB)5590000000474414 035 $a(MiAaPQ)EBC6628611 035 $a(Au-PeEL)EBL6628611 035 $a(OCoLC)1256236708 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/70780 035 $a(PPN)255883315 035 $a(EXLCZ)995590000000474414 100 $a20210901d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFrom Opinion Mining to Financial Argument Mining 210 $cSpringer Nature$d2021 210 1$aSingapore :$cSpringer Singapore Pte. Limited,$d2021. 210 4$dİ2021. 215 $a1 online resource (102 pages) 225 1 $aSpringerBriefs in Computer Science 311 $a981-16-2880-7 330 $aOpinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain. When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange. This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions. 410 0$aSpringerBriefs in Computer Science 606 $aNatural language & machine translation$2bicssc 606 $aData mining$2bicssc 606 $aAlgorithms & data structures$2bicssc 606 $aArtificial intelligence$2bicssc 606 $aInformation technology: general issues$2bicssc 610 $aNatural Language Processing (NLP) 610 $aData Mining and Knowledge Discovery 610 $aData Structures and Information Theory 610 $aArtificial Intelligence 610 $aComputer Applications 610 $aData Science 610 $aComputer and Information Systems Applications 610 $aOpen Access 610 $afinancial opinion mining 610 $atext mining in finance 610 $afinancial technology application 610 $aFinTech 610 $aargument mining in finance 610 $aopinion quality evaluation 610 $anumeral understanding 610 $aNatural language & machine translation 610 $aData mining 610 $aExpert systems / knowledge-based systems 610 $aAlgorithms & data structures 610 $aInformation theory 610 $aInformation technology: general issues 615 7$aNatural language & machine translation 615 7$aData mining 615 7$aAlgorithms & data structures 615 7$aArtificial intelligence 615 7$aInformation technology: general issues 700 $aChen$b Chung-Chi$0906903 701 $aHuang$b Hen-Hsen$0906904 701 $aChen$b Hsin-Hsi$0906905 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464443103316 996 $aFrom Opinion Mining to Financial Argument Mining$92028693 997 $aUNISA