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Analyses of Networks of Politicians Based on Linked Data: Case ParliamentSampo – Parliament of Finland on the Semantic Web

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New Trends in Database and Information Systems (ADBIS 2022)

Abstract

In parliamentary debates the speakers make reference to each other. By extracting and linking named entities from the speeches it is possible to construct reference networks and use them for analysing networks of politicians and parties and their debates. This paper presents how such a network can be constructed automatically, based on a speech corpus 2015–2022 of the Parliament of Finland, and be used as a basis for network analysis.

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Notes

  1. 1.

    https://www.w3.org/standards/semanticweb/.

  2. 2.

    https://www.clarin.eu/resource-families/parliamentary-corpora.

  3. 3.

    https://www.clarin.eu/content/parlamint-towards-comparable-parliamentary-corpora.

  4. 4.

    http://data.camera.it.

  5. 5.

    See the datamodel for speeches [22], MPs [15], and their enrichments respectively.

  6. 6.

    http://turkunlp.org/Turku-neural-parser-pipeline.

  7. 7.

    https://finto.fi/finaf/en/.

  8. 8.

    https://finto.fi/yso-paikat/en/?clang=en.

  9. 9.

    http://www.ldf.fi/dataset/pnr.

  10. 10.

    https://data.finlex.fi.

  11. 11.

    https://www.w3.org/TR/prov-o/.

  12. 12.

    https://github.com/anazalea/pySankey.

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Acknowledgements

Our work is funded by the Academy of Finland and is related to the EU project InTaVia (https://intavia.eu) and the EU COST action Nexus Linguarum (https://nexuslinguarum.eu). Computing resources of the CSC – IT Center for Science were used.

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Correspondence to Henna Poikkimäki .

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Poikkimäki, H., Leskinen, P., Tamper, M., Hyvönen, E. (2022). Analyses of Networks of Politicians Based on Linked Data: Case ParliamentSampo – Parliament of Finland on the Semantic Web. In: Chiusano, S., et al. New Trends in Database and Information Systems. ADBIS 2022. Communications in Computer and Information Science, vol 1652. Springer, Cham. https://doi.org/10.1007/978-3-031-15743-1_53

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  • DOI: https://doi.org/10.1007/978-3-031-15743-1_53

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