Last week, I had the distinct pleasure of having been invited to present at the ModelSen Workshop at the Max Planck Institute for the History of Science in Berlin. The workshop, an inspiring experience with researchers from diverse disciplines organized by Malte Vogl, Bernardo S. Buarque, Raphael Schlattmann, Aleksandra Kaye, Jascha Schmitz, Lea Weiß and Laura von Welczeck, aimed to forge pathways in understanding the historical processes of scientific knowledge evolution through innovative computational methods.
My talk, „Modeling Variation and Change in Scientific English over 300+ Years from a Communicative Perspective,“ delved into our SFB1102 work on understanding how linguistic variation optimizes information content for efficient communication, particularly in the realm of scientific writing (Project B1).
One of the pivotal aspects I discussed was our data-driven approach, a departure from traditional methods that rely on preselected, theoretically motivated linguistic features. By harnessing information-theoretic concepts, we tap into the inherent patterns within linguistic data, unearthing nuanced variations and changes often overshadowed in standard analyses due to selection of high frequency items, which we overcome with our approach. The versatility of our data-driven, information-theoretic methods makes them a powerful tool for scrutinizing change and variation in myriad contexts, a point that resonated with the workshop’s spirit of interdisciplinary enrichment.
However, the journey doesn’t end at quantitative analysis. While we can pinpoint ‚what‘ linguistic elements have shifted, understanding the ‚why‘ behind these changes often requires a deep dive into historical context, aligning with the workshop’s ethos of integrating diverse methodological approaches.
The workshop itself was a reflection to the thriving intellectual curiosity in the scientific community. With its commitment to fostering a multidisciplinary dialogue, as evidenced by the insightful White Paper published from the previous session (accessible here), the event was an invigorating space for collaborative reflection on the methodologies shaping our understanding of historical networks.
In conclusion, my experience at the MPI for the History of Science was not only an honor but also an immensely enriching platform that bolstered my belief in the need for continuous interdisciplinary dialogue. It reinforced my conviction that the future of understanding linguistic evolution relies on our collective efforts as researchers to blend computational prowess with historical insight.
Stefania Degaetano-Ortlieb 