Miriam Hurtado Bodell
@mhbodell.bsky.social
Postdoc in Analytical Sociology @Linköping University, reality TV enthusiast & ganska ”skoj”. https://mhbodell.github.io
✨ We are hiring @crestumr.bsky.social ✨ Post-doc position, up to 3 years, in a Horizon project. Profile: at the intersection of NLP & Social Sciences. More information here: shorturl.at/TxDLN 🥰 RT appreciated 🥰
Post-doctoral Position: Computational Analysis of Judicial Decisions (CREST/CNRS-Ecole polytechnique) – CSS @ IP-Paris
Site web de l'axe sciences sociales computationnelles du CREST-CNRS. Cours et tutoriels pour l'analyse des données numériques en sciences sociales.
shorturl.at
How can computational text analysis be used for building and testing social theory? @marckeuschnigg.bsky.social, @anamacanovic.bsky.social, @anmen.bsky.social & I write about how CTA is commonly used & how it might be used by sociologists in the future Out now: link.springer.com/article/10.1...
Computational Text Analysis for Building and Testing Social Theory - KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie
Digitization and advances in natural language processing have transformed how sociologists can measure, model, and interpret social life through text. We provide an overview of computational text anal...
link.springer.com
Last week @mansmag.bsky.social and I organized a workshop for researchers working with Swedish Parliamentary Data, hosted in the Riksdag. The only photo I managed to get was of @benjaminrohr.bsky.social during his great keynote. Thanks to everyone who participated and shared their research!
So excited to announce that I have been awarded a SEK2.7M Project Grant from @riksjubileumsfond.bsky.social to study the dynamics of meaning divergence! 🎉
Interested in theory-driven topic modeling? Check out our paper on using seeded LDA to analyze how the framing of immigration has evolved over 75 years.
Marc Keuschnigg@marckeuschnigg.bsky.social · 2y agoWant to avoid the tea leaves part when running topic models? The semi-supervised seeded (or constrained) topic model allows infusion of sociological knowledge when discovering meaning structures. Topics then are readily interpretable. journals.sagepub.com/doi/10.1177/...