Mark Fishman

In Waghre’s model, he has a Group A, which kicks the storm off with a post that includes some piece of content or speech that is deemed dangerous by Group B. When Group B calls it out—a behavior incentivized by algorithmic engagement, as other members of Group B reward it—Group A members will usually double down.

So many of these social-media conflicts involve the amplification of other content—the best example here is the quote tweet. An amplification of something you disagree with will create awareness and act as a signal. But that signal will likely recruit members from both sides of the conflict. It may have the intended effect of creating pressure on... See more

“The reality is that tech companies have been using automated tools to moderate content for a really long time and while it’s touted as this sophisticated machine learning, it’s often just a list of words they think are problematic,” said Ángel Díaz, a lecturer at the UCLA School of Law who studies technology and racial discrimination.

Making it easier for people to lodge their disagreements doesn't change the distribution of power; it only amplifies the voices of people who already have it.