Research

Deceptive online networks are coordinated efforts that use identity deception to pursue strategic political or financial goals. During the US 2020 elections, these networks reached at least 37 million Facebook and 3 million Instagram users, representing 15% and 2% of the platforms’ active US adult users, respectively. Only 3 networks out of 49—1 network with explicitly political aims and 2 that appeared to use politics as a lure for profit—were responsible for over 70% of users reached. Notably, accounts unaffiliated with the networks played an important role in facilitating this reach by resharing content the three networks produced. Deceptive networks, regardless of whether their goals were political or financial, reached users who were older, more conservative, more frequently exposed to content from untrustworthy sources, and spent more time on Facebook.

Starting in January 2023, Louisiana and more than 20 other states passed laws requiring age verification for websites with substantial adult content. Using Google Trends data and a synthetic control design, we examine how these laws affect the public’s digital behavior across four dimensions: searches for compliant websites, non-compliant websites, VPNs, and adult content. Three months after the laws were passed, results show a 51% decrease in searches for the main compliant platform, while searches increased for both non-compliant platform (48.1%) and VPN services (23.6%). Through multiverse analyses, we demonstrate the robustness of these findings to numerous model specifications. Our findings reveal that while regulations reduce traffic to compliant sites and likely decrease overall consumption, users adapt by shifting to providers without verification requirements. This approach provides valuable insights for policymakers around the world considering similar legislative measures of digital content regulation. Our methodology also offers a framework for real-time policy evaluation in contexts with staggered implementation.