Digital Total - Computing & Data Science an der Universität Hamburg und in der Wissenschaftsmetropole Hamburg

Using computational methods to study niche audiences

56

Nicht eingeplant

20m

Von-Melle-Park 4

Poster

Beschreibung

This study employs computational methods, utilizing YouTube user data donations and survey data, to investigate the effects of fringe bubbles on social media. These niche communities, often situated at the margins of the public sphere, are shaped by algorithmically curated biased content, potentially distorting users’ perceptions of public discourse and amplifying non-mainstream voices.
Through supervised machine learning and large language models, we automatically classify the video data and identify potential fringe bubbles. We analyze the effects of exposure to fringe issues on users’ perceptions of the public sphere, participatory behavior, and democratic values. The findings contribute to understanding the role of AI-based systems in the development and societal impact of fringe movements, such as the anti-vaccination movement.

Keywords

computational methods
media effects
filter bubbles