Treffer: An exploratory text-mining approach to analyzing DEI-related issues in eight leading architecture & design firms' publications.

Following the killing of George Floyd, Breonna Taylor and Ahmaud Arbery in 2020, a rise in social consciousness has led design firms to issue statements of commitment and increase public communication on diversity, equity, and inclusion (DEI). Simultaneously, rapid developments in data science continue to offer untapped opportunities for design researchers to efficiently explore trends that guide our industry. With these co-occurring societal shifts, first, we present a replicable step-by-step model that outlines an efficient process of data collection, cleaning and advanced big data analysis techniques to examine topics related to DEI in articles published by eight leading architecture and design firms between 2014–2023. We accompany this model with a ready-to-apply Python code that can be utilized by various research professionals to explore similar topics related to design. Second, we present findings on the most frequently discussed topics in relation to DEI is these publications. [ABSTRACT FROM AUTHOR]