eTRAP (electronic Text Reuse Acquisition Project) [Motif Identities]

eTRAP (electronic Text Reuse Acquisition Project)

From the webpage:

As the name suggests, this interdisciplinary team studies the linguistic and literary phenomenon that is text reuse with a particular focus on historical languages. More specifically, we look at how ancient authors copied, alluded to, paraphrased and translated each other as they spread their knowledge in writing. This early career research group seeks to provide a basic understanding of the historical text reuse methodology (it being distinct from plagiarism), and so to study what defines text reuse, why some people reuse information, how text is reused and how this practice has changed over history. We’ll be investigating text reuse on big data or, in other words, datasets that, owing to their size, cannot be manually processed.

While primarily geared towards research, the team also organises events and seminars with the aim of learning more about the activities conducted by our scholarly communities, to broaden our network of collaborations and to simply come together to share our experiences and knowledge. Our Activities page lists our events and we provide project updates via the News section.

Should you have any comments, queries or suggestions, feel free to contact us!

A bit more specifically, Digital Breadcrumbs of Brothers Grimm, which is described in part as:

Described as “a great monument to European literature” (David and David, 1964, p. 180), 2 Jacob and Wilhelm Grimm’s masterpiece Kinder- und Hausmärchen has captured adult and child imagination for over 200 years. International cinema, literature and folklore have borrowed and adapted the brothers’ fairy tales in multifarious ways, inspiring themes and characters in numerous cultures and languages. 3

Despite being responsible for their mainstream circulation, the brothers were not the minds behind all fairy tales. Indeed, Jacob and Wilhelm themselves collected and adapted their stories from earlier written and oral traditions, some of them dating back to as far as the seventh century BC, and made numerous changes to their own collection (ibid., p. 183) producing seven distinct editions between 1812 and 1857.

The same tale often appears in different forms and versions across cultures and time, making it an interesting case-study for textual and cross-lingual comparisons. Is it possible to compare the Grimm brothers’ Snow White and the Seven Dwarves to Pushkin’s Tale of the Dead Princess and the Seven Nights? Can we compare the Grimm brothers’ version of Cinderella to Charles Perrault’s Cinderella? In order to do so it is crucial to find those elements that both tales have in common. Essentially, one must find those measurable primitives that, if present in a high number – and in a similar manner – in both texts, make the stories comparable. We identify these primitives as the motifs of a tale. Prince’s Dictionary of Narratology describes motifs as “..minimal thematic unit[s]”, 4 which can be recorded and have been recorded in the Thompson Motif-index. 5 Hans-Jörg Uther, who expanded Aarne-Thompson classification system (AT number system) in 2004 defined a motif as:

“…a broad definition that enables it to be used as a basis for literary and ethnological research. It is a narrative unit, and as such is subject to a dynamic that determines with which other motifs it can be combined. Thus motifs constitute the basic building blocks of narratives.” (Uther, 2004)

From a topic maps perspective, what do you “see” in a tale that supports your identification of one or more motifs?

Or for that matter, how do you search across multiple identifications of motifs to discover commonalities between identifications by different readers?

It’s all well and good to tally which motifs were identified by particular readers, but clues as to why they differ requires more detail (read subjects).

Unlike the International Consortium of Investigative Journalists (ICIJ), sponsor of the Panama Papers and the Paradise Papers, the eTRAP data is available on Github.

There are only three stories, Snow White, Puss in Boots, and Fisherman and his Wife, in the data repository as of today.

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