Advanced Search
MyIDEAS: Login

Marketing Research: The Role Of Sentiment Analysis

Contents:

Author Info

  • Meena Rambocas

    ()
    (Department of Management Studies, The University of the West Indies (St. Augustine Campus))

  • João Gama

    ()
    (Laboratory of Artificial Intelligence andDecision Support & Faculty of Economics University of Porto)

Registered author(s):

    Abstract

    This article promotes sentiment analysis as an alternative research technique for collecting and analyzing textual data on the internet. Sentiment analysis is a data mining technique that systematically evaluates textual content using machine learning techniques. As a research method in marketing, sentiment analysis presents an efficient and effective evaluation of consumer opinions in real time. It allows data collection and analysis from a very large sample without hindrances, obstructions and time delays. Through sentiment analysis, marketers collect rich data on attitudes and opinion in real time, without compromising reliability, validity and generalizability. Marketers also gather feedback on attitudes and opinions as they occur without having to invest in lengthy and costly market research activities. The paper proposes sentiment analysis as an alternative technique capable of triangulating qualitative and quantitative methods through innovative real time data collection and analysis. The paper concludes with the challenges marketers can face when using this technique in their research work.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.fep.up.pt/investigacao/workingpapers/wp489.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by Universidade do Porto, Faculdade de Economia do Porto in its series FEP Working Papers with number 489.

    as in new window
    Length: 21 pages
    Date of creation: Apr 2013
    Date of revision:
    Handle: RePEc:por:fepwps:489

    Contact details of provider:
    Postal: Rua Dr. Roberto Frias, 4200 PORTO
    Phone: 351-22-5571100
    Fax: 351-22-5505050
    Email:
    Web page: http://www.fep.up.pt/
    More information through EDIRC

    Related research

    Keywords: Sentiment analysis; Machine leaning; Marketing research; Triangulation; Qualitative research; Quantitative research;

    Find related papers by JEL classification:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Gruen, Thomas W. & Osmonbekov, Talai & Czaplewski, Andrew J., 2006. "eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty," Journal of Business Research, Elsevier, vol. 59(4), pages 449-456, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:por:fepwps:489. 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: ().

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.