Deepfake technologies are a form of artificial intelligence (AI) which are based on generative adversarial networks (GANs), a development which has emerged out of deep learning (DL) and machine learning (ML) models. Using a data range which spans the years 2018 - 2021, this research explores public perceptions of deepfake technologies at scale by closely examining commentary found on the social video-sharing platform, YouTube. This open source, ground-level data documents civilian responses to a selection of user-produced, labelled deepfake content. This research fills a gap regarding public perception of this emerging technology at scale. It gauges an underrepresented set of responses in discourse to find that users demonstrate a spectrum of responses which veer between irony and concern, with greater volumes of commentary skewed towards the former. This study of user commentary also finds that YouTube as a wild space ultimately affords reflexive and critical thinking around the subject of deepfake technologies and could prove to be effective as a form of inoculation against disinformation.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:452621 |
| Date | January 2021 |
| Creators | Poon, Jessica |
| Contributors | Špelda, Petr, Fitzgerald, James |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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