# DIGIPART - A pilot dataset exploring the digitalisation of political parties

**Authors:** Marco Meloni, Fabio G. Lupato, Felix von Nostitz, Giulia Sandri, Oscar Barberà, Adrià Mompó

PMC · DOI: 10.1016/j.dib.2025.112173 · 2025-10-24

## TL;DR

This paper introduces DIGIPART, a dataset that explores how political parties in five European countries have digitalized since the pandemic.

## Contribution

The paper presents a novel dataset quantifying political party digitalization across multiple dimensions and countries.

## Key findings

- The dataset covers 76 political parties in France, Italy, Germany, the UK, and Spain.
- It includes digitalization dimensions like elections, communication, and organization.
- The dataset is intended for comparative research and democratic innovation analysis.

## Abstract

The aim of this paper is to introduce the key features of the DIGIPART – Digitalisation in Parties dataset. The DIGIPART dataset (v.1.1) provides information on the digitalisation of several key dimensions of 76 statewide and non-statewide political parties through five major European countries (France, Italy, Germany, United Kingdom, and Spain) right after the COVID-19 pandemic (2021–22). The dataset is strongly informed by previous theorisations of party digitalisation (Fitzpatrick 2021 [1], García Lupato and Meloni 2023 [2]), which divide party digitalisation into different pillars: elections, deliberation, participation, resources, communication, and organisation. The information gathered on both party features and dimensions of party digitalisation allows to explore potential variables influencing and being influenced by such phenomenon. The information was gathered and coded between 2021 and 2022 by exploring parties’ websites and manifestos, as well as press releases and secondary sources. The DIGIPART dataset offers the possibility to quantify different dimensions of party digitalisation, many of them directly related to democratic innovations. The dataset was conceived as a pilot to then scale up to other countries and regions allowing further comparative research.

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382)

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Source: https://tomesphere.com/paper/PMC12630084