  Social fragmentation transition is a transition of social states between many
disconnected communities with distinct opinions and a well-connected single
network with homogeneous opinions. This is a timely research topic with high
relevance to various current societal issues. We had previously studied this
problem using numerical simulations of adaptive social network models and found
that two individual behavioral traits, homophily and attention to novelty, had
the most statistically significant impact on the outcomes of social network
evolution. However, our previous study was limited in terms of the range of
parameter values examined, and possible interactions between multiple
behavioral traits were largely ignored. In this study, we conducted a
substantially larger-scale parameter sweep numerical experiment of the same
model with expanded parameter ranges by an order of magnitude in each parameter
dimension, resulting in a total of 116,640 simulation runs. To capture
nontrivial interactions among behavioral parameters, we modeled and visualized
the dependence of outcome measures on the model parameters using artificial
neural networks. Results show that, while the competition between homophily and
attention to novelty is still the primary determinant of social fragmentation,
another transition plane emerges when individuals have strong social conformity
behavior, which was not previously known. This implies that social
fragmentation transition can also occur in the homophily-social conformity
trade-off, the two behavioral traits that have very similar microscopic
individual-level effects but produce very different macroscopic
collective-level outcomes, illustrating the nontrivial macroscopic dynamics of
complex collective systems.
