2024 EMNLP EMNLP 2024

Enhancing Swedish Parliamentary Data: Annotation, Accessibility, and Application in Digital Humanities

Abstract

AbstractThe Swedish bicameral parliament data presents a valuable textual resource that is of interest for many researches and scholars. The parliamentary texts offer many avenues for research including the study of how various affairs were run by governments over time. The Parliament proceedings are available in textual format, but in their original form, they are noisy and unstructured and thus hard to explore and investigate. In this paper, we report the transformation of the raw bicameral parliament data (1867-1970) into a structured lexical resource annotated with various word and document level attributes. The annotated data is then made searchable through two modern corpus infrastructure components which provide a wide array of corpus exploration, visualization, and comparison options. To demonstrate the practical utility of this resource, we present a case study examining the transformation of the concept of ‘market’ over time from a tangible physical entity to an abstract idea.

🌉 Interdisciplinary Bridge — Interdisciplinary and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — corpus infrastructure
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics, Speech & Audio