IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v48y2014i4p2277-2294.html
   My bibliography  Save this article

Extending monitoring methods to textual data: a research agenda

Author

Listed:
  • Triss Ashton

    ()

  • Nicholas Evangelopoulos

    ()

  • Victor Prybutok

    ()

Abstract

Textual data has become increasingly common in business analytic data sets. While concept-based text mining offers a method of extracting meaningful information from text data, methods for monitoring of customer perceptions of business processes and products that are discussed in customer-generated documents are not immediately available. We explore the results of two text-mining algorithms and review issues observed in the data that affect uploading the results onto a newly proposed methodological monitoring platform analogous to statistical process control charts. Finally, we discuss several topics for future research in text mining. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Triss Ashton & Nicholas Evangelopoulos & Victor Prybutok, 2014. "Extending monitoring methods to textual data: a research agenda," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2277-2294, July.
  • Handle: RePEc:spr:qualqt:v:48:y:2014:i:4:p:2277-2294
    DOI: 10.1007/s11135-013-9891-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11135-013-9891-8
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    2. Peter Swanborn, 1996. "A common base for quality control criteria in quantitative and qualitative research," Quality & Quantity: International Journal of Methodology, Springer, vol. 30(1), pages 19-35, February.
    3. Ding, Chris & Li, Tao & Peng, Wei, 2008. "On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 3913-3927, April.
    4. C. Poortman & K. Schildkamp, 2012. "Alternative quality standards in qualitative research?," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(6), pages 1727-1751, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jaroslav Ráček & Jan Ministr, 2014. "Tools for Automatic Recognition of Persons and their Relationships in Unstructured Data," Acta Informatica Pragensia, University of Economics, Prague, vol. 2014(3), pages 280-287.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:48:y:2014:i:4:p:2277-2294. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://www.springer.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.