• DocumentCode
    115299
  • Title

    Recognition of NASDAQ stock symbols in Tweets

  • Author

    Kanungsukkasem, Nont ; Netisopakul, Ponrudee ; Leelanupab, Teerapong

  • Author_Institution
    Knowledge Manage. & Knowledge Eng. Lab. (KMAKE), King Mongkut´s Inst. of Technol. Ladkrabang (KMITL), Bangkok, Thailand
  • fYear
    2014
  • fDate
    30-31 Jan. 2014
  • Firstpage
    12
  • Lastpage
    16
  • Abstract
    The massive volume of Twitter data has attracted much attention of researchers to study their correlation with stock market. Tweets with stock symbols can be identified by the prefix with dollar sign or by using some complex techniques. In this paper, we focus on discovering NASDAQ stock symbols in a stream of tweets. We propose a simple but effective methodology to recognize the stock symbols. Stock symbols from NASDAQ company list, WordNet, Wikipedia and sample tweets, as well as a classic method of collocation discovery are employed to filter stock-related tweets. Experimental evaluations show that our methodology outperforms the baseline approach for recognizing NASDAQ stock symbols.
  • Keywords
    social networking (online); NASDAQ company list; Twitter; Wikipedia; WordNet; baseline approach; classic method; collocation discovery; dollar sign; sample tweets; stock market; stock symbols; Channel hot electron injection; Electronic publishing; Encyclopedias; Internet; Organizations; Portfolios; NASDAQ; Named Entity Recognition; Stock Symbol; Tweet; Twitter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge and Smart Technology (KST), 2014 6th International Conference on
  • Conference_Location
    Chonburi
  • Print_ISBN
    978-1-4799-1423-4
  • Type

    conf

  • DOI
    10.1109/KST.2014.6775386
  • Filename
    6775386