More Than a Feeling: Dataset on media sentiment regarding the Berlin Stock Exchange

Data appendix to: Lino Wehrheim/Janos Borst-Graetz/Bernhard Liebl/Manuel Burghardt/Mark Spoerer: More than a Feeling. Introducing an NLP-Based Media Sentiment Index for the Berlin Stock Exchange, 1872–1930, in: Historical Methods: A Journal of Quantitative and Interdisciplinary History 58 (2025), S: 139–159. https://doi.org/10.1080/01615440.2025.2506427. Financial economists and psychologists agree that collective sentiment plays a crucial role in financial markets. We present our newly created data for a daily aspect-based index that captures the sentiment at the Berlin Stock Exchange from 1872 to 1930, a time when Berlin was the key financial market in Germany. This index is based on market reports published every trading day in the Berliner Börsen-Zeitung, which give a verbal description of the sentiment among market participants. Due to daily publication and the long observation period, our corpus consists of about 18,000 market reports. To derive sentiment values, we apply a combination of expert annotation and machine learning. Methdologically, this data covers two novel aspects: First, we focus on both historical and highly domain-specific language, a dual challenge that thus far has rarely been addressed. As there are many similar historical sources, such as reports by chambers of commerce, our solutions will be helpful for future research. Second, we address a characteristic but neglected feature of financial texts that might be relevant also in a broader sentiment analysis context. Particularly, we focus on aspect- and entity-based sentiment analysis. Note: The data was generated in the project „More Than a Feeling: Media Sentiment as a Mirror of Investors’ Expectations at the Berlin Stock Exchange, 1872-1930“