1. Understanding the Spread of Online Misinformation That Rejects Scientific Consensus: Audiences, Platforms, and Algorithms
This project will examine the interrelationships between people's motivations for sharing information, the types of information they share (such as media sources and statements by elites of various kinds), and the affordances of video sharing platforms, particularly YouTube. The project will compile a dataset of misleading information rejecting scientific consensus on selected key issues of our time, such as, for example, climate change or health. It will undertake content analysis as well as examine audience interpretations and responses. The project will also assess the role of algorithmic power in shaping people’s exposure and responses to misinformation rejecting scientific consensus and explore how the spread and societal impact of such misinformation might be reduced.
2. What Role Do Social Media Influencers Play in Spreading Misinformation and Disinformation?
What drives people to behave in democratically-dysfunctional ways in the online environment, and how can we change this behaviour? This project will develop culturally-sensitive concepts for designing new algorithms to detect social media influencers who spread misinformation and disinformation on social media. Through a perspective attentive to the ethical and cultural implications of human-machine interactions on social media platforms, it will both improve understanding of the values embedded in platform algorithms and the role social media influencers play in spreading false information in online networks. The work will sit at the interdisciplinary intersection of computational text mining, applied data science, sociolinguistics, media theory, theories of artificial intelligence, and normative ethical theory.
Find out more, including how to apply, here.