Colloq at noon: 21. May 2025 (online): "Academia and science in the social space of the Trumpian infosphere: An exploration of U.S. periodicals, expert commentary, and (video) communication following Trumps inauguration in early 2025" by Oliver Wieczorek
Lecture by Oliver Wieczorek (University of Kassel).
Since the inauguration of Donald Trump in January 2025, science, research, and higher education in the USA have come under unprecedented attack. Executive orders targeting diversity, equity, and inclusion (DEI) initiatives, various strands of research, and elite academic institutions (such as Columbia and Harvard) have been issued, threatening academic autonomy. However, focusing solely on Trump, his administration, and its executive orders fails to capture the full picture of the ongoing struggles over the future of academia in the U.S. Instead, how academia and science therein is perceived and governed depends on:
(1) an interplay between various actors endowed with different forms of expertise—including think tanks (e.g., the Heritage Foundation), professional associations (e.g., the American Association of University Professors), science advocacy groups (e.g., the Union of Concerned Scientists), and periodicals (e.g., newspapers and opinion pieces); and
(2) societal debates shaped through social media, blogs, and podcasts.
In other words, the "Trumpian infosphere" surrounding academia is broader, more diverse, and more dynamic than it may first appear. Against this backdrop, the talk aims to:
(1) provide a macro sociological perspective on the "Trumpian infosphere"; and
(2) map—both textually and visually—key aspects of the current threats to science and higher education within broader societal discourses.
Theoretically, the approach draws on Bourdieu’s habitus-field theory, socio-semantic network analysis, and Weber’s concept of elective affinities to model the interlinkage between social fields in the reshaping of U.S. academia. Methodologically, a multimodal strategy is employed, combining textual and visual data analysis using deep neural networks (e.g., BERTopic and convolutional neural networks). The resulting elements are then subjected to relational methods (such as geometric data analysis and network analysis) to (i) map the interplay between various actors, (ii) trace how - and by whom - textual and visual representations of academia are borrowed and circulated, and, by doing so (iii) how academia is possibly reshaped in the near future.
Oliver Wieczorek is a postdoctoral researcher at INCHER since 2022. Since then, he has focused on the science of science, machine learning and multimodal methodological approaches, and educational governance.
This INCHER lecture is an online event.
If you wish to participate via Zoom please register at koch[at]incher.uni-kassel[dot]de