Abstract
PURPOSE/THESIS: We describe a new approach that addresses key challenges to multilingual corpus by merging collective human intelligence (crowdsourcing) and automated knowledge construction and extraction methods in a symbiotic fashion. APPROACH/METHODS: We use a crowdsourcing model to collect and annotate translations of the same literary text. RESULTS AND CONCLUSIONS: The model promotes a dynamic approach to archives that increases the impact of traditional research by presenting the text from a new angle, accessible to a global public.PRACTICAL IMPLICATIONS: The Global Huck project proposes a new paradigm to assess the contribution of crowdsourcing-based models for collection and annotation purposes. ORIGINALITY/VALUE: Choosing the translations of a novel as a field of study is a truly transnational and multilingual collaborative endeavor allowing us to increase our capacity to collect and organize data on a broad, transnational and multilingual scale.
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