The Facebook platform perfectly distinguishes between related assets. Algorithms use the collected information to generate trust or distrust in the user's account. When the presence of several accounts associated with the profile is detected, the user's trust is reduced to such an extent that it gets blocked, even if he does not launch anything on them. Arbitrageurs are aware of this, but no one has yet seriously investigated this fact.
How Facebook algorithms are trained and provide data
Facebook's algorithms continue to evolve and improve in recognizing huge amounts of user information. However, this process is gradual. First they learned to distinguish text entries in images, then they began to recognize audio recordings, blocking music that was copyrighted. Later, algorithms were created that easily began to recognize the content in the images, and then the technology for identifying faces. Currently, developers are actively working on training the system to recognize documents, which leads to a ban on advertising activities of some accounts and the need for business verification.
Learning algorithms is a complex process that involves searching for the right information in a data array, processing and selecting the right information, as well as transferring it to other algorithms. To train a bot, it needs to have a "data view" that includes many multifunctional applications. These applications are working together to develop artificial intelligence. One of such applications is Sparsity.
Using a sparse representation, algorithms strive to make as many features insignificant as possible and then select the most significant, determining probability, of all potential observation factors. Existing sparse models for studying huge amounts of data (including advertising) identify 42 of the most significant models, which are then investigated on a large number of existing accounts. Facebook uses this scheme to fight fraudsters.
Model Relaxedsparsemodel
Facebook AI today uses sparse representation models to ban accounts by Policy.
For example, if several accounts use the same credit card, then blocking one account leads to the ban of all others.
In addition, opening personal accounts from one IP address can lead to blocking, so you need to change the IP address every time.
Additional profiles also need to be named differently to avoid blocking.
The piggy bank of violations is gradually filling up, so even minor triggers, for example, AD ACCOUNT PAYMENT METHODS and AD ACCOUNT COUNTRY, can cause blocking.
You cannot register domain names in batches, it is better to register them as a "private person".
In addition, the FB algorithms check all the links on the landing pages and when they find a match, they all link to each other.
