It has been shown before that political debates and media influence each other. However, no studies thus far have investigated how fringe content (e.g., content from extremist online communities) can spill over into this mutual relationship despite the widespread concern regarding the potential polarizing and radicalizing power of extremist online communities. This project will extend the existing theoretical and methodological underpinnings of cross-domain information flows by offering more insights into less visible processes of content spillover via large scale content-analyses.
To this end, the project will first make use of neural networks to develop better ways to track information flows between domains, even if very different wording is used. Next, we will use web scraping and API requests to test these methods and map feedback loops between fringe communities and mainstream media focusing on content such as conspiracy theories, fake news, but also information authored by legitimate (peripheral) actors such as social movements. Finally, we will test effects-at-large that fringe content can have in the long run by tracking information flows between media, social media, and political debates. Taken together, the project will reconcile theoretical notions that analyze extremist communities through the lens of radicalization and polarization with theoretical notions that focus on the influence these groups can have on discourse at large (e.g., normalization). Read more via https://newsflows.eu/project-description/
Faculty of Social and Behavioural Sciences
CW : Corporate Communication