DIGIPART - Digitalisation in Parties dataset

  1. Meloni, Marco 1
  2. Lupato García, Fabio 2
  3. von Nostitz, Felix-Christopher 3
  4. Sandri, Giulia 3
  5. Barberà, Oscar 4
  6. Mompó, Adrià 5
  7. Blasco, Eduardo 6
  8. Centeno, Héctor 7
  1. 1 University of Southampton
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    University of Southampton

    Southampton, Reino Unido

    ROR https://ror.org/01ryk1543

  2. 2 Universidad Complutense de Madrid
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    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

  3. 3 Université Catholique de Lille
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    Université Catholique de Lille

    Lila, Francia

    ROR https://ror.org/025s1b152

  4. 4 Universitat de València
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    Universitat de València

    Valencia, España

    ROR https://ror.org/043nxc105

  5. 5 Universitat Oberta de Catalunya
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    Universitat Oberta de Catalunya

    Barcelona, España

    ROR https://ror.org/01f5wp925

  6. 6 Universidad Francisco Marroquín
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    Universidad Francisco Marroquín

    Guate, Guatemala

    ROR https://ror.org/03hrwak15

  7. 7 Universidad de La Laguna
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    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

Editor: Zenodo

Year of publication: 2024

Type: Dataset

Abstract

Despite numerous studies examining the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to address this gap by mapping parties' digitalisation. The Digitalisation in Parties (DIGIPART) dataset (v.1) comprises information on party digitalisation features from 72 parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. Compared to the initial version (v.0), which included data from 62 parties, version 1.1 of the DIGIPART dataset has been expanded to include new data on additional regional parties within these countries (n=76). The dataset, stored in Excel format (xlsx) along with a codebook, captures information and evidence from various parties, collected and coded between July 2021 and September 2022. DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov. Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.