Conference Agenda

The medieval sagas of Icelanders, celebrated for their emotionally restrained narrative style, merge prose with verse in a genre-defining prosimetrum. Traditional analysis has largely focused on the prose for emotional insights, while acknowledging that the poetry in the sagas conveys feelings more openly. This paper presents findings concerning the use of emotive language in the poetry from “The Íslendingasögur as Prosimetrum“ (ÍSP) database, which contains a comprehensive collection of quantitative data on the features of all 722 stanzas in the corpus of the sagas. The database facilitates diverse analytical explorations and assessments of correlations, allowing for a comprehensive quantitative scrutiny of established assumptions within the entire corpus of sagas. Consequently, it emerges as a robust and influential instrument for scholarly inquiry. The present study finds that internalized self-expression through first-person emotive words is relatively rare in saga poetry, representing less than a fifth of instances where emotion words are used. More frequently, self-expression is externalized, with speakers reflecting on their emotions as if they were external forces. The most prevalent usage of emotion words is in the description of others’ emotions, rather than as direct expressions of the poet’s own inner state. This suggests that the “inner world” of the poet, as scholars describe, is most often not explicitly revealed but is instead implied through these observations. Furthermore, emotive stanzas in sagas often function as performative narrative elements, complementing or contrasting with direct emotional expressions. Analysing their roles may provide deeper understanding beyond merely reflecting the poet’s psyche.

This article explores the possibilities of applying Runoregi – a user interface for browsing automatically computed textual similarity, originally designed for studying the Finnic oral tradition, in the research of Icelandic post-medieval þulur. Along with challenges common for oral poetry collections, the latter corpus presents some peculiar issues related to the specificity of the genre, as well as to the difference between Icelandic and the Finnic languages. Preliminary results show that the automatic poem clustering featured in Runoregi corresponds well to an existing scholarly analysis, while features such as dendrograms, side-by-side alignments or similar passage search are useful in exploratory research.

In the Finnic languages of Circum-Baltic region, large collections of oral poetry have been collected with periodically varying intensity from the 17th up to the 21th century. These collections include many genres, such as epic poetry, nursery rhymes, wedding songs, spells and enchantments that form part of common Finnic poetic tradition (known as runosong, Kalevala-metric song, Finnic alliterative tetrameter etc.) as well as texts in other vernacular poetic forms, and they represent a wide variety of Finnic languages and dialects, including Karelian, Estonian, Finnish, Ingrian, Ludic, Veps and Votic. While this material has been sporadically used and even seen some dedicated linguistic studies (for example, Peegel 2006, Palola 2009 and others), for large scale corpus linguistic study they have been virtually unused. One of the main reasons for this has been that it has not been clear how the poetic language in these collections relate to the linguistic variation in the Finnic-speaking region. This paper aims at alleviating that circumstance.

In this paper, we report the results of statistical analyses that seek to map the oral poetry collections to the more established corpora of spoken dialectal varieties of Finnic languages. These corpora include the dialectal section of the Finnish Syntax Archives (FSA), the Digitized Morphological Archives (DMA) and Samples of Spoken Finnish (SSF) and the Estonian Dialect Corpus (EDC). Given that the oral poetry collections form a much larger data set than any of the aforementioned dialectal corpora, and are generally thought to represent a more archaic form of language, they have considerable potential for the historical linguistic study of the languages and dialects they contain, as well as a source of general description of linguistic variation in the Finnic area. The size of the oral poetry collections available in a joint database of Finnic runosongs (FILTER database) in its entirety is little above 14M tokens, whereas the sizes of the established linguistic dialectal corpora range from 800K (SSF) to 4M (DMA) tokens and total at 7.1M tokens.

First, we characterise the oral poetry collections as a corpus and examine how much it resembles the other corpora in terms of basic corpus linguistic summary statistical overviews, such as type-token-ratios and the shapes of word frequency distributions. This verifies the general usability of the corpus and viability of application of the basic corpus linguistic tools. Then, we assess how much the different language datasets at our disposal overlap in terms of word types and geographical distribution. If the amount of overlap is small, there is very little to compare between the data sources, high level of overlap on the other hand promises more viable comparisons. We then examine how similarly the frequency distributions of high frequency types behave in all data sources and whether the oral poetry collections stand out, and if they do, do they deviate in a systematic or non-systematic way. Finally, these analyses are summarised and compared against variables concerning the geographical variation of language in each dataset. The main line of questioning here is how much the language of oral poetry reflects the spoken dialectal variety of language spoken in the areas the poems have been collected from.

We show that due to the high level of overlap in especially high frequency band word types, the oral poetry collections reliably capture dialectal variation, but when that variation is compared to the other data sources, they do not geographically align one-to-one. Rather, the oral poetry shows some systematic displacement patterns, which are interesting both linguistically and from the perspective of established folkloristic hypotheses regarding the complex development and transmission processes of the oral poetic tradition. Combined with the knowledge of the inherently considerable variation in the data, the results invite further studies, especially case studies targeting particular poetic types and geographic regions.

Variation is a core feature of folklore that reveals itself in the various aspects of folklore. For example, content, style, performance, usage and functions of folkloric communication slightly differ individually as well as regionally at the same time manifesting a recognizable similarity of phenomena in larger or smaller scale. According to Juri Lotman (1977), a specific type of aesthetics prevails in folklore, which he calls the “aesthetics of sameness”: it is considered beautiful if the artistic expression does not deviate too much from the general standard, the creativity is appreciated but within certain limits.

The digitization and datafication of folklore materials enables us to explore the variation with the help of statistical and computational methods. Due to the layered nature of folkloric variation, as well as the unevenness in collection history, this is a complex task. Within a FILTER project funded by Finnish Academy we have invented some methods and procedures to handle variation in large multilingual corpus of poetic texts. In addition to the purely folkloric variation, underlying linguistic variation poses an additional challenge. In order to detect similar but still slightly different verses we have successfully applied a similarity detection method based on cosine similarity of verse bigrams (Janicki et al 2023). By clustering the verses by their similarity measures, we will get verse clusters that are close enough to verse types. Verse types that occur often nearby each other tend to form the adjacency groups of (1) stereotypic formulae, (2) motifs or (3) even the whole songs.

According to the theory of oral-formulaic composition (Parry 1971; Lord 1991) that laid the foundation for understanding oral epic composition, the poetic composition in the conditions of oral transmission relies on the mastery of essential elements such as formulas, themes, and story-patterns. These recurring patterns, encompassing form, meaning, and narrative, transcend mere repetition; they are the fundamental building blocks of the oral tradition.

Exploration of variation among the texts of a song type has been one of the central tasks in geographical–historical research that in the 19th century was a central method in folkloristics. Although the aims of folkloristic research have changed since, it is still a relevant task to figure out the main features and branches of a large number of similar texts. We have been looking for ways to do this computationally and as one possible solution we have applied network visualization to adjacency measures of verse clusters. In network view, the modularity groups are able to represent the most common sub motifs and regional branches of the plot. Thus far, we have applied these procedures in the Finnic runosong tradition. In our current presentation, we will expand this to Ukrainian dumas, to find out (1) if the methods we have used are applicable for the analysis of oral poetry in more universal terms; and (2) if there are considerable differences in variation patterns of Slavic and Finnic poetic traditions.

Dumas form a lyric-epic genre where the songs tell about historical or social events in Ukraine (Lanovyk & Lanovyk 2005: 261). For research material we use a corpus of Ukrainian Folk Dumas compiled on the basis of large academic publication (Skrypnyk 2019). Our analysis focuses on the duma "Escape of three brothers from the city of Azov, from Turkish captivity," preserved in 74 variants.This specific heroic narrative touches on the themes of captivity, escape, and death in the steppes, making it a unique and fascinating aspect of Ukrainian oral folklore. Despite its origins in a single escape incident, the duma gained widespread popularity, forming so many variants and becoming a symbol of national tragedy for the Ukrainian people. Its enduring appeal lies in the narrative's rich content, which goes beyond a family tragedy and encapsulates a broader national situation.

Ultimately, this computational exploration attempts to bridge the gap between traditional scholarship and modern computational methods, offering a novel perspective on the dynamic and interconnected nature of oral traditions. The insights gained from this study have implications for preserving cultural diversity, fostering cross-cultural understanding, and advancing computational approaches in the study of folk songs.

This paper describes in-progress work to quantitatively analyse the development of the Finnish national epic Kalevala, both in terms of the oral poetry sources used, as well as in terms of the development of the final edition through multiple preparatory publications and manuscripts. In terms of methodological development, the paper relates to prior research on how to visualise relations between texts. However, the particular nature of oral poetry and the editing process at play here precludes using any of the established methods directly, leading instead to the development of complementary approaches.