In an explorative manner, this article uses a data-driven digital history set-up to focus on media political issues in Sweden during the second half of the twentieth century. By distant reading and topic modeling a dataset of 3100 Swedish Government Official Reports between 1945 and 1989—a corpus of some 87 million tokens—the article gives a new perspective of how the Swedish state examined and discussed media in general and media politics in particular. Topic modeling is a computational method to study latent themes or discourses in a dataset by accentuating words that tend to co-occur and together create different topics. Via a computational interrogation of the dataset in a Jupyter Lab environment a number of media topics can be detected. They include the most common words for each media topic, but also reveal temporal periodizations when media political issues were foremost discussed as well as other societal topics that media was related to.

本文以探索性的方式使用数据驱动的数字历史设置来关注 20 世纪下半叶瑞典的媒体政治问题。通过对 1945 年至 1989 年间 3100 份瑞典政府官方报告的数据集（包含约 8700 万个标记的语料库）进行远程阅读和主题建模，这篇文章为瑞典政府如何检查和讨论一般媒体，特别是媒体政治提供了一个新视角。主题建模是一种计算方法，通过强调倾向于同时出现并共同创建不同主题的单词来研究数据集中的潜在主题或话语。通过在 Jupyter Lab 环境中对数据集进行计算查询，可以检测到许多媒体主题。它们包括每个媒体主题最常用的词，