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dc.contributor.authorChen, Chung-Chi
dc.contributor.authorHuang, Hen-Hsen
dc.contributor.authorChen, Hsin-Hsi
dc.description.abstractOpinion 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.
dc.relation.ispartofseriesSpringerBriefs in Computer Science
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language & machine translation
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UN Databases::UNF Data mining
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UM Computer programming / software development::UMB Algorithms & data structures
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligence
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UB Information technology: general issues
dc.subject.otherNatural Language Processing (NLP)
dc.subject.otherData Mining and Knowledge Discovery
dc.subject.otherData Structures and Information Theory
dc.subject.otherArtificial Intelligence
dc.subject.otherComputer Applications
dc.subject.otherData Science
dc.subject.otherComputer and Information Systems Applications
dc.subject.otherOpen Access
dc.subject.otherfinancial opinion mining
dc.subject.othertext mining in finance
dc.subject.otherfinancial technology application
dc.subject.otherargument mining in finance
dc.subject.otheropinion quality evaluation
dc.subject.othernumeral understanding
dc.subject.otherNatural language & machine translation
dc.subject.otherData mining
dc.subject.otherExpert systems / knowledge-based systems
dc.subject.otherAlgorithms & data structures
dc.subject.otherInformation theory
dc.subject.otherInformation technology: general issues
dc.titleFrom Opinion Mining to Financial Argument Mining
oapen.imprintSpringer Singapore
oapen.grant.number[grantnumber unknown]

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open access
Except where otherwise noted, this item's license is described as open access