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Paper short abstract:

Word clouds have become a common feature in higher education teaching. The “Wolf Rapsody in C-Major” case study introduces how applying a generative machine learning approach to the analysis of ethnographic data can contribute to softening the polarised debate about the return of large carnivores.

Paper long abstract:

Word clouds have become a common feature in higher education teaching. Intrigued by their popularity, this contribution sets out to explore the viability and usefulness of “word cloud seeding” in ethnographic anthropological practice. To what effect? The “Wolf Rapsody in C-Major” case study introduces how applying a generative machine learning approach to the analysis of ethnographic data can contribute to breaking down the polarised debate surrounding the return of large carnivores to Western continental Europe. The traveling exhibition “Kushti Bok” (meaning “Good hunger”, or “all is well” in the Romani language) by David Weiss serves as a testbed for establishing the effectiveness of word clouds that seek to visualize the “vibe” of the core problematics of “Rewilding Europe”, as well as the newer sensibilities of the Anthropocene Zeitgeist at street level. Of particular concern to this elucidation of ecological sentiments are the paradoxes and dilemmas arising from the Green Deal’s endeavor to safeguard biodiversity, while legislators deliberate on weakening the protected status of the wolf in the European Union. The alphabetical letters “C” (in English), respectively “K” in German, provide the entry point. Why this linguistic detail matters to the programmer as well as to the anthropologist relates to the underlying wordplay (Bock/Bok). The “C” is the key to decoding this artistic intervention made possible by the consonant shift and end syllable devoicing – a perk that seeds the clouds presented here.