Today, we’re sharing an update on the enforcement actions we’ve taken since our last monthly report on coordinated inauthentic behavior (CIB). This includes both our September CIB report and a set of enforcement actions we’ve taken in the last few days. In total, we are publishing our findings about 10 networks — six operations we removed in September, most of which we already announced, and four new operations that we removed since October 1, including those we disabled this morning. In each case, the people behind this activity coordinated with one another and used fictitious accounts and personas as a central part of their operations to mislead people about who they are and what they are doing, and that was the basis for our action. When we investigate and remove these operations, we focus on behavior rather than content, whether they’re foreign or domestic, and regardless of who’s behind them or what they post. Over the past three years, we’ve shared our findings about coordinated inauthentic behavior we detect and remove from our platforms. Earlier this year, we started publishing regular CIB reports where we share information about the networks we take down over the course of each month to make it easier for people to see progress we’re making in one place. In some cases, like today, we also share our findings soon after our enforcement. The latest takedowns we are announcing today will also be included in our October report. You can find more information about our previous CIB enforcement actions here. Before we share the details on each network, here are a few trends to note. More than half of the networks we’re sharing today targeted domestic audiences in their countries and many of them were linked to groups and individuals associated with politically affiliated actors in the US, Myanmar, Russia, Nigeria, Philippines and Azerbaijan. Over the past three years, we’ve seen and taken action against domestic political actors around the world using CIB. We know these actors will continue to attempt to deceive and mislead people, including by making particular viewpoints appear more widely supported or criticized than they are, or by targeting influencers to unwittingly amplify their narratives. Two of the networks we’re sharing today engaged primarily in commenting on content — relying on real people, not automation — to create the perception of widespread support of their narratives by leaving comments on posts by media entities