1887

oa Chapter 13. Quantitative analysis of translations in Spanish-language periodical publications (1900–1945)

A methodological proposal

image of Chapter 13. Quantitative analysis of translations in Spanish-language periodical publications (1900–1945)

This paper addresses the quantification of literary production in Spanish between 1900 and 1945. To obtain quantitative data, we must consider catalogue records both of main libraries and of newspaper and periodicals libraries. The latter preserve literary magazines that feature articles and translations from peripheral authors who were overshadowed or forgotten by historical narrative. Given the absence of proper cataloguing in newspaper and periodicals libraries, it is necessary to develop a workflow that enables massive and accurate searches. The aim of the proposed methodology is to build a meta catalogue that allows to search for authors and works together with translators or illustrators. Only this way will we be able to obtain an overall image of that literary period.

  • Affiliations: 1: Universitat Oberta de Catalunya; 2: 300.000 km / Institute of Advanced Studies of Catalonia

References

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    2011 “Machine Learning for Document Structure Recognition”. Studies in Computational Intelligence370: 221–47. 10.1007/978‑3‑642‑22613‑7_12
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    2015 “Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution”. Edited by Alain Barrat . PLOS ONE10 (10): e0137041. doi:  10.1371/journal.pone.0137041.
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    2015 “Visions and Open Challenges for a Knowledge-Based Culturomics”. International Journal on Digital Libraries15 (2–4): 169–87. 10.1007/s00799‑015‑0139‑1
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    2003 “Using Artificial Neural Networks to Identify Headings in Newspaper Documents”. InProceedings of the International Joint Conference on Neural Networks, 2003, 3:2283–87. IEEE. 10.1109/IJCNN.2003.1223767
    https://doi.org/10.1109/IJCNN.2003.1223767 [Google Scholar]

References

  1. Andersen, Timothy L. , and Wei Zhang
    2003 “Features for Neural Net Based Region Identification of Newspaper Documents”. InSeventh International Conference on Document Analysis and Recognition, 2003. Proceedings, 1:403–7. IEEE Comput. Soc.. 10.1109/ICDAR.2003.1227698
    https://doi.org/10.1109/ICDAR.2003.1227698 [Google Scholar]
  2. Chen, Xiaotian
    2012 “Google Books and WorldCat: A Comparison of Their Content”. Online Information Review36 (4): 507–516. doi:  10.1108/14684521211254031.
    https://doi.org/10.1108/14684521211254031 [Google Scholar]
  3. Cristianini, Nello , Thomas Lansdall-Welfare , and Gaetano Dato
    2018 “Large-Scale Content Analysis of Historical Newspapers in the Town of Gorizia 1873–1914”. Historical Methods: A Journal of Quantitative and Interdisciplinary History51 (3): 139–64. 10.1080/01615440.2018.1443862
    https://doi.org/10.1080/01615440.2018.1443862 [Google Scholar]
  4. Gulordava, Kristina , and Marco Baroni
    2011 “A Distributional Similarity Approach to the Detection of Semantic Change in the Google Books Ngram Corpus”. InProceedings of the GEMS 2011 Workshop on Geometrical Models of Natural Language Semantics, edited by Sebastian Pado and Yves Peirsman , 67–71. Edinburgh. https://www.aclweb.org/anthology/W11-2508
    [Google Scholar]
  5. Heilbron, Johan
    1999 “Towards a Sociology of Translation: Book Translations as a Cultural World-System”. European Journal of Social Theory2 (4): 429–44. 10.1177/136843199002004002
    https://doi.org/10.1177/136843199002004002 [Google Scholar]
  6. Juola, P.
    2013 “Using the Google N-Gram Corpus to Measure Cultural Complexity”. Literary and Linguistic Computing28 (4): 668–75. 10.1093/llc/fqt017
    https://doi.org/10.1093/llc/fqt017 [Google Scholar]
  7. Koplenig, Alexander
    2015 “The Impact of Lacking Metadata for the Measurement of Cultural and Linguistic Change Using the Google Ngram Data Sets – Reconstructing the Composition of the German Corpus in Times of WWII”. Digital Scholarship in the Humanities32 (1): 169–88. 10.1093/llc/fqv037
    https://doi.org/10.1093/llc/fqv037 [Google Scholar]
  8. Lamarca Morell, Dolors , and Eugènia Serra Aranda
    2005 “L’estratègia de La Biblioteca de Catalunya En Projectes Digitals”. Item: Revista de Biblioteconomia i Documentació, no.41: 41–53. doi: https://www.raco.cat/index.php/Item/article/view/40866/68116.
    [Google Scholar]
  9. Lansdall-Welfare, Thomas , Saatviga Sudhahar , James Thompson , Justin Lewis , FindMyPast Newspaper Team, and Nello Cristianini
    2017 “Content Analysis of 150 Years of British Periodicals.” Proceedings of the National Academy of Sciences of the United States of America114 (4): E457–65. 10.1073/pnas.1606380114
    https://doi.org/10.1073/pnas.1606380114 [Google Scholar]
  10. Michel, Jean-Baptiste , Yuan Kui Shen , Aviva Presser Aiden , Adrian Veres , Matthew K. Gray , The Google Books Team , Joseph P. Pickett ,
    2011 “Quantitative Analysis of Culture Using Millions of Digitized Books.” Science (New York, N.Y.)331 (6014): 176–82. 10.1126/science.1199644
    https://doi.org/10.1126/science.1199644 [Google Scholar]
  11. Paaß, Gerhard , and Iuliu Konya
    2011 “Machine Learning for Document Structure Recognition”. Studies in Computational Intelligence370: 221–47. 10.1007/978‑3‑642‑22613‑7_12
    https://doi.org/10.1007/978-3-642-22613-7_12 [Google Scholar]
  12. Pechenick, Eitan Adam , Christopher M. Danforth , and Peter Sheridan Dodds
    2015 “Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution”. Edited by Alain Barrat . PLOS ONE10 (10): e0137041. doi:  10.1371/journal.pone.0137041.
    https://doi.org/10.1371/journal.pone.0137041 [Google Scholar]
  13. Tahmasebi, Nina , Lars Borin , Gabriele Capannini , Devdatt Dubhashi , Peter Exner , Markus Forsberg , Gerhard Gossen , et al
    2015 “Visions and Open Challenges for a Knowledge-Based Culturomics”. International Journal on Digital Libraries15 (2–4): 169–87. 10.1007/s00799‑015‑0139‑1
    https://doi.org/10.1007/s00799-015-0139-1 [Google Scholar]
  14. Zhang, Wei , and Timothy L. Andersen
    2003 “Using Artificial Neural Networks to Identify Headings in Newspaper Documents”. InProceedings of the International Joint Conference on Neural Networks, 2003, 3:2283–87. IEEE. 10.1109/IJCNN.2003.1223767
    https://doi.org/10.1109/IJCNN.2003.1223767 [Google Scholar]
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