From Opinion Mining to Financial Argument Mining
Materialtyp:
ArtikelSerie: Utgivningsinformation: Springer Nature Springer Singapore [Imprint] 2021Beskrivning: 1 electronic resource (95 p.)Innehållstyp: - text
- computer
- online resource
- 9789811628818
- Computing and Information Technology
- Information technology: general topics
- Computer programming / software engineering
- Algorithms & data structures
- Databases
- Data mining
- Computer science
- Artificial intelligence
- Natural language and machine translation
- Algorithms & data structures
- Artificial Intelligence
- Computer Applications
- Computer and Information Systems Applications
- Data Mining and Knowledge Discovery
- Data Science
- Data Structures and Information Theory
- Data mining
- Expert systems
- FinTech
- Information technology
- Information theory
- Natural Language Processing (NLP)
- Natural language & machine translation
- Open Access
- U Computing and Information Technology
- UB Information technology
- UM Computer programming
- UMB Algorithms and data structures
- UN Databases
- UNF Data mining
- UY Computer science
- UYQ Artificial intelligence
- UYQL Natural language and machine translation
- argument mining in finance
- financial opinion mining
- financial technology application
- general issues
- general topics
- knowledge-based systems
- numeral understanding
- opinion quality evaluation
- software engineering
- text mining in finance
- thema EDItEUR
Open Access Unrestricted online access star
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.
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Creative Commons Licence cc by cc https://creativecommons.org/licenses/by/4.0/
eng
Freely available e-book