  The heterogeneity of the influence processes is an important feature of
social systems: how we perceive social influence and how we influence other
individuals is heavily influenced by our opinion and non-opinion attributes.
The latter include demographic, cultural, and structural (how we are embedded
in social networks) characteristics. Furthermore, the results of the influence
processes may also depend on how similar the interacting individuals are in
terms of their features. This paper addresses this issue and elaborates on an
agent-based model that is sensitive to the individual characteristics, both
opinion and non-opinion ones. The model is fortified with a ranking algorithm
that mimics the ranking algorithms widely adopted in real-world online social
networks. For the resulting model, I elaborate a mean-field approximation that
describes the behavior of the model at the macroscopic level via an autonomous
system of ordinary differential equations. The properties of this system are
thoroughly studied.
