Daniel Klug
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Recent Grants
Grant: Close
Preventing Viral Racism on TikTok
Open Date: 2022-03-01
Close Date: 2023-12-01
Grant: Close
Entwicklung und Evaluation einer Web-Applikation (trAVis-school) zur Analyse von audiovisuellen Medienangeboten im schulischen Musikunterricht
Open Date: 2016-04-01
Close Date: 2019-03-01
Grant: Close
Scripted Reality-Programmangebote in Fernsehen und Internet. Vergleichende Produktions-, Produkt- und Rezeptionsanalysen für den Senderaum (deutschsprachige) Schweiz
Open Date: 2014-04-01
Close Date: 2016-03-01
Grant: Close
Bild-Text-Ton-Analysen am Beispiel der Gattung Videoclip. Entwicklung eines integrierten Analyseinstrumentariums zur Interpretation von Musikvideos
Open Date: 2008-07-01
Close Date: 2011-03-01
Articles (3)
Social media users have long been aware of opaque content moderation systems and how they shape platform environments. On TikTok, creators increasingly utilize algospeak to circumvent unjust content restriction, meaning, they change or invent words to prevent TikTok’s content moderation algorithm from banning their video (e.g., “le$bean” for “lesbian”). We interviewed 19 TikTok creators about their motivations and practices of using algospeak in relation to their experience with TikTok’s content moderation. Participants largely anticipated how TikTok’s algorithm would read their videos, and used algospeak to evade unjustified content moderation while simultaneously ensuring target audiences can still find their videos. We identify non-contextuality, randomness, inaccuracy, and bias against marginalized communities as major issues regarding freedom of expression, equality of subjects, and support for communities of interest. Using algospeak, we argue for a need to improve contextually informed content moderation to valorize marginalized and tabooed audiovisual content on social media.
Year:
2023
Year:
2021
Year:
2020
Collaborators (1)
Elke Schlote
Lecturer
University of Applied Sciences of the Grisons
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