  In social media, we communicate through pictures, videos, short codes, links,
partial phrases. It is a rich, and digitally documented communication channel
that relies on a multitude of media and forms. These channels are sorted by
algorithms as organizers of discourse, mostly with the goal of channeling
attention. In this research, we used Twitter to study the way Media
Architecture is discussed within the community of architects, designers,
researchers and policy makers. We look at the way they spontaneously share
opinions on their engagement with digital infrastructures, networked places and
hybrid public spaces. What can we do with all those opinions? We propose here
the use of text-mining and machine learning techniques to identify important
concepts and patterns in this prolific communication stream. We discuss how
such techniques could inform the practice and emergence of future trends.
