Speaker
Description
Recent events, including Meta’s removal of third-party moderators, indicate the growing need for policymakers to engage with extremist content online as well as with the role that social media platforms play in its dissemination. A key issue, however, is the adaptability and fluidity of the online space, allowing extremist actors to circumvent moderation. This research aims to provide additional insight into how extremist content and social media platforms relate to each other, to better understand how extremist content moves through social media, and to provide new methods through which to track extremist content online. In doing so, Social Network Analysis (SNA) is introduced as one approach to identify key extremist nodes/accounts as well as recurring themes and patterns associated to extremist content, which can allow for more efficient targeting.
Drawing on early SNA findings concerning TikTok’s ‘For You Page’, this research discusses how far-right and masculinist content evolve according to different user interests, algorithmic recommendation, and different political events, notably the presidential election of Donald Trump but also the delay of TikTok’s ban. The data highlights how extremist content can increase without user consent and indicates a relatively stable level of extremist content irrespective of user interests.
| What discipline or branch of humanities or social sciences do you identify yourself with? | International Security, Science and Technology Studies |
|---|---|
| If you are submitting an Open Panel proposal, have you included all four abstracts in attachment? | No, I am submitting a Closed Panel abstract |
| Are you a PhD student or early-career researcher? | Yes |
