IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v58y2024i3d10.1007_s11135-023-01776-8.html
   My bibliography  Save this article

The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys

Author

Listed:
  • Jan Karem Höhne

    (Leibniz University Hannover)

  • Christoph Kern

    (Ludwig-Maximilians-University Munich)

  • Konstantin Gavras

    (Nesto Software GmbH)

  • Stephan Schlosser

    (University of Göttingen)

Abstract

Web surveys completed on smartphones open novel ways for measuring respondents’ attitudes, behaviors, and beliefs that are crucial for social science research and many adjacent research fields. In this study, we make use of the built-in microphones of smartphones to record voice answers in a smartphone survey and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to predict respondents’ level of interest (i.e., disinterest, neutral, and high interest) based on their voice answers, which expands the opportunities for researching respondents’ engagement and answer behavior. We conducted a smartphone survey in a German online access panel and asked respondents four open-ended questions on political parties with requests for voice answers. In addition, we measured respondents’ self-reported survey interest using a closed-ended question with an end-labeled, seven-point rating scale. The results show a non-linear association between respondents’ predicted level of interest and answer length. Respondents with a predicted medium level of interest provide longer answers in terms of number of words and response times. However, respondents’ predicted level of interest and their self-reported interest are weakly associated. Finally, we argue that voice answers contain rich meta-information about respondents’ affective states, which are yet to be utilized in survey research.

Suggested Citation

  • Jan Karem Höhne & Christoph Kern & Konstantin Gavras & Stephan Schlosser, 2024. "The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(3), pages 2907-2927, June.
  • Handle: RePEc:spr:qualqt:v:58:y:2024:i:3:d:10.1007_s11135-023-01776-8
    DOI: 10.1007/s11135-023-01776-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-023-01776-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11135-023-01776-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:58:y:2024:i:3:d:10.1007_s11135-023-01776-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.