The Sound of respondents: Predicting respondents’ level of Interest with voice data in smartphone surveys

Höhne, Jan Karem ; Kern, Christoph ; Gavras, Konstantin ; Schlosser, Stephan

Document Type: Working paper
Year of publication: 2022
The title of a journal, publication series: SSRN Working Paper Series
Place of publication: Rochester, NY
Publication language: English
Institution: School of Social Sciences > Social Data Science and Methodology (Keusch 2022-)
Subject: 300 Social sciences, sociology, anthropology
Keywords (English): answer behavior , interest prediction , natural language processing , open-ended questions , smartphone , voice recordings
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 smartphone surveys and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to infer respondents’ level of interest, which may expand 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. 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.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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