  Among the several approaches that have been attempted at studying opinion
dynamics, the Sznajd model provides some particularly interesting features,
such as its simplicity and ability to represent some of the mechanisms believed
to be involved in opinion dynamics. The standard Sznajd model at zero
temperature is characterized by converging to one stable state, implying null
diversity of opinions. In the present work, we develop an approach -- namely
the adaptive Sznajd model -- in which changes of opinion by an individual (i.e.
a network node) implies in possible alterations in the network topology. This
is accomplished by allowing agents to change their connections preferentially
to other neighbors with the same state. The diversity of opinions along time is
quantified in terms of the exponential of the entropy of the opinions density.
Several interesting results are reported, including the possible formation of
echo chambers or social bubbles. Additionally, depending on the parameters
configuration, the dynamics may converge to different equilibrium states for
the same parameter setting, which suggests that this phenomenon can be a phase
transition. The average degree of the network strongly influences the resultant
opinion distribution, which means that echo chambers are easily formed in lower
connected systems.
