IDEAS home Printed from https://ideas.repec.org/a/ids/ijemre/v17y2026i2p149-175.html

Review helpfulness in online settings: an analysis of informational and emotional content

Author

Listed:
  • Betul Durkaya Kurtcan
  • Sebnem Burnaz

Abstract

Online reviews are increasingly becoming a helpful resource for customers in their purchase decisions. Their helpfulness appears to be an important asset to evaluate the effectiveness of online reviews. Based on elaboration likelihood model (ELM), this study focuses on the factors in online consumer reviews that can influence review helpfulness and how the impact generated by these factors varies according to product type. Several analytical processes are applied to gather information on review content, such as feature extraction, sentiment analysis, and emotion analysis. An analysis of 1,673 reviews from Amazon.com shows that rating, length, image count, polarity, anger, fear, joy, and trust in reviews affect review helpfulness positively while subjectivity, informativeness, anticipation, sadness, and surprise in reviews have negative influence on review helpfulness. Product type is found to moderate the impact of review length, image count, review subjectivity, review informativeness, and emotions such as sadness, disgust, and joy on review helpfulness.

Suggested Citation

  • Betul Durkaya Kurtcan & Sebnem Burnaz, 2026. "Review helpfulness in online settings: an analysis of informational and emotional content," International Journal of Electronic Marketing and Retailing, Inderscience Enterprises Ltd, vol. 17(2), pages 149-175.
    • Handle: RePEc:ids:ijemre:v:17:y:2026:i:2:p:149-175
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=151735
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:ids:ijemre:v:17:y:2026:i:2:p:149-175. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=43 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.