Financial text mining: Supporting decision making using web 2.0 content

Hsin Min Lu, Hsinchun Chen, Tsai Jyh Chen, Mao Wei Hung, Shu Hsing Li

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

The significant use of online technologies has facilitated the creation of large amounts of textual data. The continuous textual data requires the development of a surveillance system that can collect, filter, extract, quantify, and analyze relevant information from the Internet. Finance-related textual content is divided into three categories, the first includes forums, blogs, and wikis, the second category includes news and research reports and the third category involves finance-related content generated by firms. Several firms maintain their own Web sites as a communication channel with consumers and investors. Public companies are required to submit their filings to the Edgar system, which is publicly accessible on the Web. The growing body of Web 2.0 content can facilitate the implementation of near real-time monitoring system and allow financial institutions to benefit from the continues textual data.

Original languageEnglish (US)
Article number5456414
Pages (from-to)78-82
Number of pages5
JournalIEEE Intelligent Systems
Volume25
Issue number2
StatePublished - Aug 5 2010

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Lu, H. M., Chen, H., Chen, T. J., Hung, M. W., & Li, S. H. (2010). Financial text mining: Supporting decision making using web 2.0 content. IEEE Intelligent Systems, 25(2), 78-82. [5456414].