04819nam a22006015i 4500 978-981-16-2881-8 DE-He213 20210624035743.0 cr nn 008mamaa 210520s2021 si | s |||| 0|eng d 9789811628818 978-981-16-2881-8 10.1007/978-981-16-2881-8 doi QA76.9.N38 UYQL bicssc COM073000 bisacsh UYQL thema 006.35 23 Chen, Chung-Chi. author. (orcid)0000-0003-3680-9277 https://orcid.org/0000-0003-3680-9277 aut http://id.loc.gov/vocabulary/relators/aut From Opinion Mining to Financial Argument Mining [electronic resource] / by Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen. 1st ed. 2021. Singapore : Springer Singapore : Imprint: Springer, 2021. X, 95 p. 24 illus., 21 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda SpringerBriefs in Computer Science, 2191-5768 Introduction -- Modeling Financial Opinions -- Sources and Corpora -- Organizing Financial Opinions -- Numerals in Financial Narratives -- FinTech Applications -- Perspectives and Conclusion. Open Access 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. Natural language processing (Computer science). Data mining. Data structures (Computer science). Artificial intelligence. Application software. Natural Language Processing (NLP). https://scigraph.springernature.com/ontologies/product-market-codes/I21040 Data Mining and Knowledge Discovery. https://scigraph.springernature.com/ontologies/product-market-codes/I18030 Data Structures and Information Theory. https://scigraph.springernature.com/ontologies/product-market-codes/I15009 Artificial Intelligence. https://scigraph.springernature.com/ontologies/product-market-codes/I21000 Computer Applications. https://scigraph.springernature.com/ontologies/product-market-codes/I23001 Huang, Hen-Hsen. author. (orcid)0000-0001-9169-3081 https://orcid.org/0000-0001-9169-3081 aut http://id.loc.gov/vocabulary/relators/aut Chen, Hsin-Hsi. author. (orcid)0000-0001-9757-9423 https://orcid.org/0000-0001-9757-9423 aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) Springer Nature eBook Printed edition: 9789811628801 Printed edition: 9789811628825 SpringerBriefs in Computer Science, 2191-5768 https://doi.org/10.1007/978-981-16-2881-8 ZDB-2-SCS ZDB-2-SXCS ZDB-2-SOB Computer Science (SpringerNature-11645) Computer Science (R0) (SpringerNature-43710)