04510nam 22008173 450 99646444310331620231110233502.0981-16-2881-5(CKB)5590000000474414(MiAaPQ)EBC6628611(Au-PeEL)EBL6628611(OCoLC)1256236708(oapen)https://directory.doabooks.org/handle/20.500.12854/70780(PPN)255883315(EXLCZ)99559000000047441420210901d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierFrom Opinion Mining to Financial Argument MiningSpringer Nature2021Singapore :Springer Singapore Pte. Limited,2021.©2021.1 online resource (102 pages)SpringerBriefs in Computer Science 981-16-2880-7 Opinion 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.SpringerBriefs in Computer Science Natural language & machine translationbicsscData miningbicsscAlgorithms & data structuresbicsscArtificial intelligencebicsscInformation technology: general issuesbicsscNatural Language Processing (NLP)Data Mining and Knowledge DiscoveryData Structures and Information TheoryArtificial IntelligenceComputer ApplicationsData ScienceComputer and Information Systems ApplicationsOpen Accessfinancial opinion miningtext mining in financefinancial technology applicationFinTechargument mining in financeopinion quality evaluationnumeral understandingNatural language & machine translationData miningExpert systems / knowledge-based systemsAlgorithms & data structuresInformation theoryInformation technology: general issuesNatural language & machine translationData miningAlgorithms & data structuresArtificial intelligenceInformation technology: general issuesChen Chung-Chi906903Huang Hen-Hsen906904Chen Hsin-Hsi906905MiAaPQMiAaPQMiAaPQBOOK996464443103316From Opinion Mining to Financial Argument Mining2028693UNISA