Finding the structure of parliamentary motions in the Swedish Riksdag 1971–2015
Artikel i vetenskaplig tidskrift, 2023

The current increase in the number of large, open sets of unstructured textual data has created both opportunities and challenges for social scientists. Here, we explore if and how we can use such data by looking at a dataset of over 144,000 documents used by parliamentary committees in Sweden. Of these, we aim to understand: (a) the topical content of these motions, (b) how these topics have changed over time, and (c) how these topics differ across political parties. To do so, we use a Structural Topic Model, which allows us to not only find the topics using the textual data itself, but also to include the documents’ metadata, such as authorship and date of publication. Doing so, we find 30 topics, which we combine into 9 broader themes. We find that these themes often rise and fall in popularity in line with historical events, and relate to the various political parties as we would expect. Throughout our analysis, we provide a step-by-step overview of how to use structural topic models in practice and also how to handle the type of dataset we use here.

Författare

Sebastianus Cornelis Jacobus Bruinsma

Chalmers, Data- och informationsteknik, Data Science och AI

Moa Johansson

Chalmers, Data- och informationsteknik, Data Science och AI

Quality and Quantity

0033-5177 (ISSN) 1573-7845 (eISSN)

Vol. In press

Ämneskategorier

Språkteknologi (språkvetenskaplig databehandling)

Historia

DOI

10.1007/s11135-023-01802-9

Mer information

Senast uppdaterat

2024-01-09