Data & Code: Using Deepfakes for Experiments in the Social Sciences – A Pilot Study
GESIS, Cologne. Data File Version 1.0.0, https://doi.org/10.7802/2467
Abstract: The advent of deepfakes – the manipulation of audio records, images and videos based on deep learning techniques – has important implications for science and society. Current studies focus primarily on the detection and dangers of deepfakes. In contrast, less attention is paid to the potential of this technology for substantive research – particularly as an approach for controlled experimental manipulations in the social sciences. In this paper, we aim to fill this research gap and argue that deepfakes can be a valuable tool for conducting social science experiments. To demonstrate some of the ... more Availability: Restricted Access
Subject area: Sociology
Methodology
Date(s) of Data Collection: 2022; 2022
Universe: The experiment was embedded in an online bachelor course at Friedrich-Alexander University Erlangen-Nuremberg with 39 students. After one instruction for all respondents, the students were randomly assigned into one of two groups (one treatment group and one control group).
Sampling Procedure: Total Universe / Complete enumeration
Mode of Data Collection: Web-based experiment
Bibliographic information
Primärforschende, Institution: Eberl, Andreas; Universität Erlangen-Nürnberg | Kühn, Juliane; Universität Erlangen-Nürnberg | Wolbring, Tobias; Universität Erlangen-Nürnberg
Publication year: 2022
DOI: 10.7802/2467
Study number: SDN-10.7802-2467
Project funder: Financial support from the Emerging Talents Initiative (ETI) from the University of Erlangen-Nuremberg
Publisher: GESIS, Cologne
Versions
Current Version: 1.0.0, https://doi.org/10.7802/2467
Reference publications
Publications: Eberl, A., Kühn, J. and Wolbring, T. (2022) Using Deepfakes for Experiments in the Social Sciences – A Pilot Study. Frontiers in Sociology, 7:907199. https://doi.org/10.3389/fsoc.2022.907199
