The official documents of the government-general of Taiwan are from the official Taiwan document collection of the Japanese government from before World War II. The documents have been preserved in good condition, and although the official documents of the Japanese government about Japan from that time remain sealed, the Taiwan documents have been published openly. Thus, the documents that are available for historical study are scarce and valuable. Although these documents are being digitized continuously by researchers at Chukyo University, we used the already digitized catalog of the documents from the Meiji era for a quantitative analysis in order to obtain an overview of the enormous number of administrative documents. Through this analysis we were able to detect the chronological shifts in topics of the administrative documents from that time. In addition, we added geographical information based on the place names, and, depending on the regions, extracted characteristics related to the themes of the documents. The goal of this research is to investigate the usefulness of the digitized text of official documents for historical and social studies. The methods used for the analysis in this research can in the future be applied to all of the digitized texts in this collection for more precise and comprehensive quantitative analyses.
Computational film analysis combines statistics, data science, information visualization, and computer science with the analytical approaches and domain knowledge of the study of film to frame and answer questions about form and style in the cinema. In this article I illustrate the visualisation and analysis of the soundtrack of the trailer for the Korean horror film Into the Mirror (2003). Using the spectrogram and normalized aggregated power envelope to show how the sound design of the trailer evolves over time and functions at different scales. I address a range of practical considerations relevant to the methods demonstrated here relating to the use of mono versus stereo audio files, the use of different sampling rates, and audio normalization. A supporting website with the code for the statistical programming language R used in this analysis is available at https://rpubs.com/nr62_rp33/CFA-into-the-mirror.