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                <title>Big Translation History. Data Science Applied to the Circulation of Translated Literature</title>
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                        <surname>Roig Sanz</surname>
                        <forename>Diana</forename>
                    </persName>
                    <affiliation>ICREA/UOC, Spain</affiliation>
                    <email>dsanzr@uoc.edu</email>
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                <edition>
                    <date>2021-09-10T13:24:00Z</date>
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                <publisher>Elisabeth Burr, University of Leipzig</publisher>
                <address>
                    <addrLine>Beethovenstr. 15</addrLine>
                    <addrLine>04107 Leipzig</addrLine>
                    <addrLine>Germany</addrLine>
                    <addrLine>Elisabeth Burr</addrLine>
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            <p>This lecture proposes the term Big Translation History (BTH) to describe a translation history that can be analysed computationally and that I define as involving: (1) large-scale research (geographical and chronological); (2) massive data understood as big data, accompanied by little data, and drawing on a wide range of often heterogeneous and non-structured sources; and (3) the use of computational techniques as part of the research process, and for the production of knowledge, rather than helping only with visualisation of data. I advance the hypothesis that one of the main possibilities of BTH, as a conceptual framework and a methodology, is to help decentralize translation history and literary and cultural history, in a broad sense. The lecture goes on to present an analysis of the circulation of literary translations and the agents involved in the Spanish-speaking world between 1898 and 1945 as a case study in BTH, but it can be applied to other languages, periods, and geographical scales.</p>
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