The computational humanities and social sciences (CHSS) increasingly rely on large, text-rich datasets – from digital corpora and learner corpora to discourse-annotated datasets and historical archives – yet researchers often struggle with the limitations of existing tools for large-scale data processing, modeling, and reproducibility. This minisymposium introduces Julia as a powerful, expressive, and high-performance solution for CHSS research. We showcase how Julia’s strengths (speed, a solid type system, first-class multiple dispatch, and seamless interoperability with Python and R) enable both rapid experimentation and production-grade analysis. Through case studies ranging from corpus statistics and collocation networks to mixed-effects modeling of experimental data and large-scale language data pipelines, we highlight existing Julia packages and other emerging ones such as TextAssociations.jl and demonstrate how Julia can substantially expand what researchers in the humanities and social sciences can achieve. The minisymposium aims to build bridges between Julia developers and CHSS scholars while fostering a new community of users working with rich textual, linguistic, and sociocultural data.
3 organizers: Alexandros Tantos (Aristotle University of Thessaloniki), Julia Mueller (Universitaet Freiburg) and Axel Bohmann (Universitaet Koeln)