  Among different aspects of social networks, dynamics have been proposed to
simulate how opinions can be transmitted. In this study, we propose a model
that simulates the communication in an online social network, in which the
posts are created from external information. We considered the nodes and edges
of a network as users and their friendship, respectively. A real number is
associated with each user representing its opinion. The dynamics starts with a
user that has contact with a random opinion, and, according to a given
probability function, this individual can post this opinion. This step is
henceforth called post transmission. In the next step, called post
distribution, another probability function is employed to select the user's
friends that could see the post. Post transmission and distribution represent
the user and the social network algorithm, respectively. If an individual has
contact with a post, its opinion can be attracted or repulsed. Furthermore,
individuals that are repulsed can change their friendship through a rewiring.
These steps are executed various times until the dynamics converge. Several
impressive results were obtained, which include the formation of scenarios of
polarization and consensus of opinions. In the case of echo chambers, the
possibility of rewiring probability is found to be decisive. However, for
particular network topologies, with a well-defined community structure, this
effect can also happen. All in all, the results indicate that the post
distribution strategy is crucial to mitigate or promote polarization.
