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  3. 10. Analysing deepfakes: A discourse-semiotic approach
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10. Analysing deepfakes: A discourse-semiotic approach

  • Marcus Scheiber(author)
Chapter of: Imagery of Hate Online(pp. 221–242)
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Metadata
Title 10. Analysing deepfakes
SubtitleA discourse-semiotic approach
ContributorMarcus Scheiber(author)
DOIhttps://doi.org/10.11647/obp.0447.10
Landing pagehttps://www.openbookpublishers.com/books/10.11647/obp.0447/chapters/10.11647/obp.0447.10
Licensehttps://creativecommons.org/licenses/by/4.0/
CopyrightMarcus Scheiber;
PublisherOpen Book Publishers
Published on2025-05-02
Long abstractManipulated communicates in the form of altered images and/or videos—so-called deepfakes—threaten to fundamentally undermine belief in the authenticity of visual artefacts (online). Deepfakes allow the face of a person in an image to be transferred to the face of another person, or to depict actions that a person has never taken in order to spread forms of disinformation, as well as hate and conspiracy ideologies. As advancing technologies in the field of AI have made deepfakes more accessible and easier to use, and, in many cases, users no longer recognise them as fakes, deepfakes can act as a catalyst for echo chambers. Even though AI-based solutions already exist that have made enormous progress in recognising deepfakes, they are often trained on isolated contexts and are unable to capture the complexity of visual practices (of digital communication), or incorporate the semantic nuances of implicit patterns into their identification processes. The construction of meaning of visual artefacts is always embedded in social contexts of action, which are both prefigured by collective knowledge and entail certain practices of use. Within this context, this chapter aims to present a qualitative approach that promises to complement the existing quantitative AI-based approaches with a discourse-semiotic perspective.
Page rangepp. 221–242
LanguageEnglish (Original)
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Landing PageFull text URLPlatform
PDFhttps://www.openbookpublishers.com/books/10.11647/obp.0447/chapters/10.11647/obp.0447.10Landing pagehttps://books.openbookpublishers.com/10.11647/obp.0447.10.pdfFull text URL
HTMLhttps://www.openbookpublishers.com/books/10.11647/obp.0447/chapters/10.11647/obp.0447.10Landing pagehttps://books.openbookpublishers.com/10.11647/obp.0447/ch10.xhtmlFull text URLPublisher Website
Contributors

Marcus Scheiber

(author)
PhD Researcher at University of Vechta
https://orcid.org/0009-0006-1714-2015

Marcus Scheiber is a discourse semiotician specialising in critical discourse analysis, internet linguistics, multimodal research and antisemitism research. He started his academic career at the Universities of Heidelberg and Bern, and as a visiting researcher and lecturer at the University of Mumbai. He received his MA from the University of Heidelberg in 2018 with a thesis about internet memes. He is currently working on a Ph.D. project at the University of Vechta and the University of Vienna, in which he is investigating how the communication format of memes is used for antisemitic communication strategies in the digital sphere.

References
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  2. Chong, Alicia Tsui Ying, Hui Na Chua, Muhammed Basheer Jasser and Richard T. K. Wong, 2023. “Bot or Human? Detection of DeepFake Text with Semantic, Emoji, Sentiment and Linguistic Features”. Shah Alam: IEEE 13th International Conference on System Engineering and Technology (ICSET), 205–210. https://doi.org/10.1109/icset59111.2023.10295100
  3. Fallis, Don, 2021. “The Epistemic Threat of Deepfakes”. Philosophy & Technology, 34 (4), 623–643. https://doi.org/10.1007/s13347-020-00419-2
  4. Felder, Ekkehard, 2007. “Von der Sprachkrise zur Bilderkrise. Überlegungen zum Text-Bild-Verhältnis im Paradigma der pragma-semiotischen Textarbeit”. In: Friedrich Müller (ed.), Politik (Neue) Medien und die Sprache des Rechts. Berlin: Duncker und Humblot GmbH, 191–219.
  5. Geise, Stephanie and Marion G. Müller, 2015. Grundlagen der visuellen Kommunikation. München: UVK Verlagsgesellschaft. https://doi.org/10.36198/9783838524146
  6. Groh, Matthew, Ziv Epstein, Chaz Firestone and Rosalind Picard, 2022. “Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowds”. Proceedings of the National Academy of Sciences, 119 (1), 1–11. https://doi.org/10.1073/pnas.2110013119
  7. Große, Franziska, 2011. Bild-Linguistik. Grundbegriffe und Methoden der linguistischen Bildanalyse in Text- und Diskursumgebungen. Frankfurt am Main: Lang.
  8. Klug, Nina-Maria, 2016. “Multimodale Text- und Diskurssemantik”. In: Nina-Maria Klug and Hartmut Stöckl (eds), Handbuch Sprache im multimodalen Kontext. Berlin: De Gruyter, 165–189. https://doi.org/10.1515/9783110296099
  9. ―, and Hartmut Stöckl, 2016. “Sprache im multimodalen Kontext”. In: Nina-Maria Klug and Hartmut Stöckl (eds), Handbuch Sprache im multimodalen Kontext. Berlin: De Gruyter, 242–264. https://doi.org/10.1515/9783110296099
  10. Köller, Wilhelm, 2004. Perspektivität und Sprache. Zur Struktur von Objektivierungsformen in Bildern, im Denken und in der Sprache. Berlin: De Gruyter. https://doi.org/10.1515/9783110919547.
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  12. ―, 2010. Multimodality. A Social Semiotic Approach to Contemporary Communication. London: Routledge. https://doi.org/10.1080/10572252.2011.551502
  13. Manjula, A.K., R. Thirukkumaran, K. Hrithik Raj, Ashwin Athappan and R. Paramesha Reddy, 2022. “Deep Fakes Image Animation Using Generative Adversarial Networks”. Chennai International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), 1–6. https://doi.org/10.1109/ACCAI53970.2022.9752506
  14. Matuszewski, Paweł and Gabriella Szabó, 2019. “Are echo chambers based on partisanship? Twitter and political polarity in Poland and Hungary”. Social Media + Society, 5 (2). https://doi.org/10.1177/2056305119837671
  15. Sachs-Hombach, Klaus, 2003. Das Bild als kommunikatives Medium. Elemente einer allgemeinen Bildwissenschaft. Köln: Herbert von Halem.
  16. Scheiber, Marcus, Troschke, Hagen and Krasni, Jan, 2024. Vom kommunikativen Phänomen zum gesellschaftlichen Problem: Wie Antisemitismus durch Memes viral wird. In: Susanne Kabatnik, Lars Bülow, Marie-Luis Merten and Robert Mroczynski (eds), Pragmatik multimodal (= Studien zur Pragmatik, Bd. 7), 257–284.
  17. Scholz, Oliver Robert, 2005. “Bilder: konventionell, aber nicht maximal arbiträr”. In: Stefan Majetschak (eds), Bild-Zeichen. Perspektiven einer Wissenschaft vom Bild. München: Wilhelm Fink, 63–76.
  18. Seymour, Michael, Kai Riemer, Lingyao Yuan and Alan R. Dennis, 2022. “Beyond Deep Fakes”. Communications of the ACM, 66 (10), 56–67. https://doi.org/10.1145/3584973
  19. Stöckl, Hartmut, 2004. Die Sprache im Bild – Das Bild in der Sprache. Zur Verknüpfung von Sprache und Bild im massenmedialen Text. Konzepte. Theorien. Analysemethoden. Berlin: De Gruyter. https://doi.org/10.1515/9783110201994
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  23. Wollebæk, Da, Rune Karlsen, Kari Steen-Johnsen and Bernard Enjorlas, 2019. ”Anger, fear, and echo chambers: The emotional basis for online behavior”. Social Media + Society, 5 (2). https://doi.org/10.1177/2056305119829859

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