Abstract
AbstractRecommendation systems have become ubiquitous, and they actively participate in creating our individual and collective identity. In this paper, the diffusion of climate change information has been studied based on YouTube’s recommendation system and the political media landscape. The YouTube channels of CNN, BBC News and Fox News, as the most popular channels, respectively, for Left, Center and Right parties, were explored using web scraping and social network analysis to check what kind of recommended content will pop up if a user looks for climate change videos. Using an agent-based modeling approach, the competition between Left, Center and Right media in pushing their own narrative of climate change in society was simulated. The results suggest YouTube’s recommendation algorithm is highly biased since most of the recommended content was from the same channel fitting their own political agenda. The agent-based modeling indicates the size of a network is a decisive factor in further spread of a message as Left media always dominated Center and Right media in pushing their own perspective on climate change regardless of higher weights assigned to Right media. This study shed light on how public perception on climate change can be shaped by recommendation systems and digital companies.
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems
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