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020 _a9789811628818
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024 7 _a10.1007/978-981-16-2881-8
_2doi
050 4 _aQA76.9.N38
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072 7 _aCOM073000
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082 0 4 _a006.35
_223
100 1 _aChen, Chung-Chi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aFrom Opinion Mining to Financial Argument Mining
_h[electronic resource] /
_cby Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen.
250 _a1st ed. 2021.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2021.
300 _aX, 95 p. 24 illus., 21 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5776
505 0 _aIntroduction -- Modeling Financial Opinions -- Sources and Corpora -- Organizing Financial Opinions -- Numerals in Financial Narratives -- FinTech Applications -- Perspectives and Conclusion.
506 0 _aOpen Access
520 _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.
650 0 _aNatural language processing (Computer science).
650 0 _aData mining.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aApplication software.
650 0 _aArtificial intelligence.
650 1 4 _aNatural Language Processing (NLP).
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aData Science.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aArtificial Intelligence.
700 1 _aHuang, Hen-Hsen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aChen, Hsin-Hsi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811628801
776 0 8 _iPrinted edition:
_z9789811628825
830 0 _aSpringerBriefs in Computer Science,
_x2191-5776
856 4 0 _uhttps://doi.org/10.1007/978-981-16-2881-8
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-SOB
999 _c37399
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