Examining the Role of YouTube Production and Consumption Dynamics on the Formation of Extreme Ideologies
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Abstract (arXiv)
The relationship between content production and consumption on algorithm-driven platforms like YouTube plays a critical role in shaping ideological behaviors. While prior work has largely focused on user behavior and algorithmic recommendations, the interplay between what is produced and what gets consumed, and its role in ideological shifts remains understudied. In this paper, we present a longitudinal, mixed-methods analysis combining one year of YouTube watch history with two waves of ideological surveys from 1,100 U.S. participants. We identify users who exhibited significant shifts toward more extreme ideologies and compare their content consumption and the production patterns of YouTube channels they engaged with to ideologically stable users. Our findings show that users who became more extreme consumed have different consumption habits from those who do not. This gets amplified by the fact that channels favored by users with extreme ideologies also have a higher affinity to produce content with a higher anger, grievance and other such markers. Lastly, using time series analysis, we examine whether content producers are the primary drivers of consumption behavior or merely responding to user demand.
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References · 12
- 2018Datasheets for Datasetscited by 1,386
- 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 801
- 2019Auditing Radicalization Pathways on YouTubecited by 53
- 2021Algorithmic Amplification of Politics on Twittercited by 38
- 2019Algorithmic Extremism: Examining YouTube's Rabbit Hole of Radicalizationcited by 13
- 2020Examining the consumption of radical content on YouTubecited by 13
- 2022YouTube, The Great Radicalizer? Auditing and Mitigating Ideological Biases in YouTube Recommendationscited by 10
- 2023Causally estimating the effect of YouTube's recommender system using counterfactual botscited by 8
- 2020The Grievance Dictionary: Understanding Threatening Language Usecited by 7
- 2023The Amplification Paradox in Recommender Systemscited by 6
- 2019To Act or React: Investigating Proactive Strategies For Online Community Moderationcited by 3
- 2024Uncovering the Interaction Equation: Quantifying the Effect of User Interactions on Social Media Homepage Recommendationscited by 1
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