“Being moved” by music in the 19th century

• Applicant: Professor Dr. Frank Hentschel
• Subject Area: Musicology
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 573993043

Research context. This interdisciplinary project aims to explore the experience of “being moved” (Ergriffensein) by music as it is documented in German-language text sources from the long 19th century (1789–1914). “Being moved” appears as a prominent emotional concept, evoked in numerous text sources from that time such as concert reviews, reports, and commentaries on music. Its relevance beyond the 19th century is corroborated by the fact that it is dealt with intensely in the current psychology of aesthetics. Hypotheses. First, we expect that it is possible to extract certain musical features which were likely to elicit the emotion of “being moved” as reported in 19th-century sources (Hypothesis 1). Second, we assume that there are several different kinds of music (defined by different sets of musical features), rather than one homogeneous type, that elicited this emotion (Hypothesis 2). Methods. The project combines methods of text coding and analysis (especially Semantic Network Analysis) with the manual and automated digital encoding of music analyses and machine-learning approaches for clustering and classification in order to assess the impact of musical features on the emergence of the experience of “being moved.” As our text corpus, we shall examine a broad range of music journals provided by two prominent and easily searchable digital archives, ANNO and RIPM. The text sources containing references to “being moved” will be coded manually (text features and metadata) using the software MAXQDA. In parallel, we shall annotate the music referred to in these sources as eliciting the affect of “being moved” with respect to such musical features as harmony, melody, rhythm, instrumentation, texture, and form. In a binary classification machine-learning task, we will determine the predictive power of these features with respect to class membership, distinguishing documents containing references to “being moved” from a control sample. Level of originality. In addressing our hypotheses, our project follows up on own previous research, seeking to combine—for the first time—corpus-based music analysis and the corpus-based study of historical documents of the 19th century describing listening responses to the music in an attempt to reveal correlations between musical features and affective states. Researchers involved. The two principal investigators bring to the table a host of qualifications beneficial for the project, including expertise in music historical research, music analysis, corpus research, and the Digital Humanities. Both the text analytic and the music analytic branches are supported by one PhD student each. A postdoctoral researcher with a strong background in computational humanities will carry out the quantitative analysis and machine-learning parts.

• DFG Programme: Research Grants
• International Connection: Austria
• Cooperation Partner: Professor Dr. Markus Neuwirth