  Opinion formation has been gaining increasing research interests recently,
and various models have been proposed. These models, however, have their
limitations, among which noticeably include (i) it is generally assumed that
adjacent nodes holding similar opinions will further reduce their difference in
between, while adjacent nodes holding significantly different opinions would
either do nothing, or cut the link in between them; (ii) opinion mutation,
which describes "opinion changes not due to neighborhood influences" in real
life, is typically random. While such models enjoy their simplicity and
nevertheless help reveal lots of useful insights, they lack the capability of
describing many complex behaviors which we may easily observe in real life. In
this paper, we propose a new bit-string modeling approach. Preliminary study on
the new model demonstrates its great potentials in revealing complex behaviors
of social opinion evolution and formation.
