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Visualizing and Analyzing Networks of Named Entities in Biographical Dictionaries for Digital Humanities Research

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Computational Linguistics and Intelligent Text Processing (CICLing 2019)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13451))

Abstract

This paper shows how named entity extraction and network analysis can be used to examine biographies individually and in groups to aid historians in biographical and prosopographical research. For this purpose a reference network of 13 100 biographies in the collections of the Biographical Centre of the Finnish Literature Society was created, based on links between the biographies as well as automatically extracted named entities found in the texts. The data was published in a SPARQL endpoint as a Linked Data knowledge graph on top of which network analytic tools were created and analysis were done showing the usefulness of the approach in Digital Humanities. The reference graph has been utilized for network analysis to examine egocentric networks of individual persons as well as networks among groups of people in prosopography. The data and tools presented are in use since autumn 2018 in the semantic portal BiographySampo that has had tens of thousands of users.

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Notes

  1. 1.

    Online at www.biografiasampo.fi; see project homepage https://seco.cs.aalto.fi/projects/biografiasampo/en/ for further info and publications.

  2. 2.

    Prosopography is a method that is used to study groups of people through their biographical data. The goal of prosopography is to find connections, trends, and patterns from these groups.

  3. 3.

    Actually, the biographies in our case study come from several separate databases, including the general National Biography of Finland as a core, supplemented with four other thematic dictionaries [16].

  4. 4.

    https://kansallisbiografia.fi/english/national-biography.

  5. 5.

    http://hipla.fi.

  6. 6.

    http://developers.google.com/maps/.

  7. 7.

    https://github.com/Traubert/FiNer-rules/blob/master/finer-readme.md.

  8. 8.

    http://persistence.uni-leipzig.org/nlp2rdf/specification/core.html.

  9. 9.

    http://dublincore.org/documents/dcmi-terms/.

  10. 10.

    Denoted with prefix nbf.

  11. 11.

    https://finto.fi/yso-paikat/en/.

  12. 12.

    The view currently lists only sentences that contain manually added HTML links.

  13. 13.

    https://korp.csc.fi/.

  14. 14.

    https://linkedjazz.org/.

  15. 15.

    https://www.dbpedia-spotlight.org/demo/.

  16. 16.

    https://cloud.gate.ac.uk/.

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Acknowledgments

Our research was part of the Severi project (http://seco.cs.aalto.fi/projects/severi), funded mainly by Business Finland. Thanks to Mikko Kivelä for inspirational discussions and CSC - IT Center for Science for computational resources.

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Authors and Affiliations

  1. Semantic Computing Research Group (SeCo), Aalto University, Espoo, Finland

    Minna Tamper, Petri Leskinen & Eero Hyvönen

  2. HELDIG – Helsinki Centre for Digital Humanities, University of Helsinki, Helsinki, Finland

    Eero Hyvönen

Authors
  1. Minna Tamper
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  2. Petri Leskinen
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  3. Eero Hyvönen
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Correspondence to Minna Tamper .

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  1. Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

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Tamper, M., Leskinen, P., Hyvönen, E. (2023). Visualizing and Analyzing Networks of Named Entities in Biographical Dictionaries for Digital Humanities Research. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2019. Lecture Notes in Computer Science, vol 13451. Springer, Cham. https://doi.org/10.1007/978-3-031-24337-0_15

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