Cybersecurity for Democracy
Cybersecurity for Democracy is a multi-university center for problem-driven research and research-driven policy. We conduct cutting-edge cybersecurity research to better understand the distorting effects of algorithms and AI tools on large online networks and work with platforms and regulators to help all parties understand the implications of our findings and develop solutions.
Featured content
Cybersecurity for Democracy (C4D) has released two important papers, one that analyzes online hate and harassment networks targeting election officials and one that recommends how online platforms can ensure they are not contributing to potential political violence, including against election workers.
New Lab Notebook from Laura Edelson: Instagram and TikTok both say they have different feed experiences for users based on whether they are adults or minors. To find out, I tested these platforms as a 23 year old and 13 year old user, and found that the TikTok experiences was very different between my adult and teen 'personas', but the Instagram Reels experiences were not.
Our newest policy paper is out: "Preventing Tech-Fueled Political Violence: What online platforms can do to ensure they do not contribute to election-related violence," co-authored by our Senior Policy Fellow Yael Eisenstat.
Lab Notebook: Getting to know the TikTok API. Earlier this year, I got access to the TikTok API. I've been using it to explore the conversation on the platform about the conflict in Gaza.
Yaël Eisenstat Joins Cybersecurity for Democracy as Senior Policy Fellow, Focusing on Democratic Discourse and AI-Powered Political Messaging.
Lab Notebook: Predicting Virality. The ability to predict viral content has clear ramifications for content moderation and harm mitigation. Under the resource constraints that most Trust and Safety teams face, knowledge of which adverse content (e.g. hate, harassment, misinformation etc.) will garner the most engagement, enables more efficient allocation of time and effort to address them. We found that looking at the engagement alone without considering post or account features, we are able to predict with a binary F1 of 0.8 whether a post’s final engagement would be in the top 1% by hours 13–17.
How you can help
Join our newsletter
Keep up to date with our latest news, blog posts, and projects.
Latest
Recent Research
Instagram and TikTok both say they have different feed experiences for users based on whether they are adults or minors. To find out, I tested these platforms as a 23 year old and 13 year old user, and found that the TikTok experiences was very different between my adult and teen 'personas', but the Instagram Reels experiences were not.
More research