Miriam Hurtado Bodell

At the Institute for Analytical Sociology, I am a PhD-student in the Mining for Meaning research project.

Large Scale Computational Text Analysis for Sociology

My research focus on the role of media in public discourse regarding immigration and integration using large scale computational text analysis.

Of special interest for me are the dynamics behind the creation of in- and out-groups, and the emergence and diffusion of shared understandings on political issues, and the impact of these processes on individual’s behavior. Specifically, I’m interested in adopting and modifying methodological frameworks from statistics and natural language processing to conduct sociological research.

Academic Degrees

• MSc of Science in Statistics and Machine Learning, 2016

• BSc of Science in Statistics, 2014

• BSc of Science in Political Science, majoring in Economics, 2014

Read more about the project

Publications

2024

Miriam Hurtado Bodell, Måns Magnusson, Marc Keuschnigg (2024) Seeded Topic Models in Digital Archives: Analyzing Interpretations of Immigration in Swedish Newspapers, 1945-2019 Sociological Methods & Research (Article in journal) Continue to DOI
Miriam Hurtado Bodell, Måns Magnusson, Marc Keuschnigg (2024) Seeded Topic Models in Digital Archives: Analyzing Interpretations of Immigration in Swedish Newspapers, 1945-2019 Sociological Methods & Research (Article in journal) Continue to DOI
Miriam Hurtado Bodell (2024) Mining for Meaning: using computational text analysis for social inquiry

2022

Miriam Hurtado Bodell, Mans Magnusson, Sophie Muetzel (2022) From Documents to Data: A Framework for Total Corpus Quality SOCIUS, Vol. 8, Article 23780231221135523 (Article in journal) Continue to DOI

2019

Miriam Hurtado Bodell, Martin Arvidsson, Måns Magnusson (2019) Interpretable Word Embeddings via Informative Priors Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), p. 6324-6330, Article D19-1661 (Conference paper)

Organisation

News