  We introduce a minimal opinion formation model, which is quite flexible and
can reproduce a broad variety of the existing micro-influence assumptions and
models. At the same time, the model can be easily calibrated on real data, upon
which it imposes only a few requirements. From this perspective, our model can
be considered as a bridge, connecting theoretical studies on opinion formation
models and empirical research on social dynamics. We investigate the model
analytically by using mean-field approximation and numerically. Our analysis is
exemplified by recently reported empirical data drawn from an online social
network. Employing these data for the model calibration, we demonstrate that
the model may reproduce fragmented and polarizing social systems. Furthermore,
we manage to generate an artificial society that features properties
quantitatively and qualitatively similar to those observed empirically at the
macro scale. This ability became possible after we had advanced the model with
two important communication features: selectivity and personalization
algorithms.
