>In policy 1, the authors propose banning relatively small hate clusters. Banning the largest hate cluster would be predicted to lead to the formation of a new large cluster from the myriad small ones. Banning whole groups of users, regardless of the size of the groups, can result in outrage in the hate community and allegations against social-media platforms that rights to FREE SPEECH are being suppressed. To avoid that, policy 2 instead recommends banning a small number of users selected at random from online hate clusters.
Boil a Frog and slowly kill freedom of speech.
>Policy 3 leverages the finding that clusters self-organize from an initially disordered group of users; it recommends that platform administrators promote the organization of clusters of anti-hate users, which could serve as a ‘human immune system’ to fight and counteract hate clusters.
Gradually Infecting boards with plebbit users over these past few years/months
>Policy 4 exploits the fact that many hate groups online have opposing views. The policy suggests that the platform administrators introduce an artificial group of users to encourage interactions between hate clusters that have opposing views, with a view to the hate clusters subsequently battling out their differences among themselves.
Divide and conquer, false flag jewry

From nature, Strategies for combating online hate An analysis of the dynamics of online hate groups on social-media platforms reveals why current methods to ban hate content are ineffective, and provides the basis for four potential strategies to combat online hate.