Great New Design: How Do We Talk about Media Architecture in Social Media
This work addresses the challenge of extracting insights from unstructured social media data for the architecture and design community, but it is incremental as it applies existing methods to a new dataset.
The researchers tackled the problem of analyzing discussions about Media Architecture on social media, specifically Twitter, by applying text-mining and machine learning techniques to identify key concepts and patterns from opinions shared by architects, designers, researchers, and policymakers.
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.