  We develop an agent-based model in order to understand agent/node behaviors
that generate social media networks. We use simple rules to synthetically
generate a backcloth (friend/follow) network collected using Twitter's API. The
Twitter network was collected using seeds for known terrorist propaganda
accounts in 2015. Model parameter adjustments were made to reproduce the
collected network's summary statistics, stylized facts and general structural
measures. We produced an approximate network in line with the general
properties of our collected data. We present our findings with a focus on the
challenging aspects of this reproduction. We find that while it is possible to
generate a social media network utilizing a few simple rules, numerous
challenges arise requiring departure from the agent viewpoint and the
development of more useful methods. We present numerous weaknesses and
challenges in our reproduction and propose potential solutions for future
efforts.
