Additional material to the manuscript "Debating E-Voting throughout Europe: Constitutional Structures, Parties' Concepts, and Europeans' Perceptions"

This repository contains the scripts and raw data collected for the paper "Constitutional Structures for E-Voting throughout Europe", published at Frontiers for Political Science, 5, https://www.frontiersin.org/articles/10.3389/fpos.2023.982558/full

The study investigates the distribution of e-voting perceptions throughout Europe by analysing the constitutions, party manifestos, and Eurobarometer surveys.

Abstract

Techno-optimists agree that e-voting lies at the heart of implementing e-government and digitalisation into democratic structures. However, we do not know much about the specific extent to which e-voting exists in European constitutions, even after one generation of intense debate about its possible implementation. Perceptions on e-voting matter because of the omnipresent digital transformation and discussions about how democracies (could) digitalise. How do party policies resemble e-voting on the national and European levels? E-voting represents a crucial, bottom-up part of top-down e-government and, through this, of digital transformation. The example of the "e-state" Estonia proves the relevance: e-voting has been in (legal) practice since 2005, and research can take much empirical evidence from this laboratory for digital innovation. The fact that Estonia is an exception to the rule within the EU member states explains the comparative approach to the (possible) legal framework for e-participation. With focussing on liberal democracies' constitutional predefinitions, voting procedures in the virtual age have not been compared yet.

We approach the question of "legalistic opportunity structures" by relying on constitutions of European member states and parties´ policies. Using a dictionary approach, our research design analyses the constitutions and manifestos of parties running for the European elections. Therefore, national constitutions and party manifestos are part of this study, which we analyse using several mixed-methods approaches. Our results have the broader implications that we need to study in more detail what the digital transformation and the constitutionalisation of electronic decision-making entail to develop a digital democracy and link it to a public sphere throughout Europe. In the end, we conclude by analysing whether or not the EU pushes its member states to e-voting and will implement e-voting for European elections.

The .Rmd-File is in a pre-beta stadium, so please, add remarks and recommendations to improve the code (code review) here to the discussion. Thank you. The first plot of the distribution of e-voting through party platforms was produced using the following R-script:

Short R-Script to reproduce Figure 1

# Loading libraries
library(tidyverse)
library(dplyr)
library(plotly)
library(readr)
library(ggplot2)
library(hrbrthemes)

# reading data
data <- read_csv("https://raw.githubusercontent.com/isaborucki/e-voting_constitutions/main/data/Manifesto_Coding-Search_Results.csv")
View(data)

# investigate data
evoteyear <- table(data$Land,data$Jahr) 
# this shall check whether we have 
# absolute counts for the countries coded in our material

View(evoteyear)

# build data frame containing keyword hits in manifestos per countries per year
df <- data %>% 
        count(Land, Jahr)

# Plot the distribution of keywords mentions over years per country
Freq <- data %>% 
      group_by(Land) %>% 
      summarise(n = n()) %>% 
      mutate(Freq = n/sum(n)) %>% 
  mutate(Land = factor(Land, Land))

# To plot, we use ggplot, first only a scatterplot to see how the unique entries 
# are distributed over the years

  ggplot(data, aes(x=Jahr, y=Land))+
    geom_point(alpha = 0.5) +
    theme_minimal()
  
# Being more concrete we add bubbleplots to assess the range of said total 
# counts of mentions wihtin the manifestos. 
# Boxplots and violins with mean and median are outlined for visibility 
# reasons but left to play around with. 

ggplot(df,
       aes(x=Jahr, y=Land, size=n))+
  geom_point(alpha = 0.5) +
  #geom_boxplot() +
  #geom_rug(col="steelblue",alpha=0.1, linewidth=1.5) +
  #geom_violin()+
  #stat_summary(fun.y = mean, colour = "darkblue")+
  #stat_summary(fun.y = median, colour = "black")+
  labs(x = "Year",
       y = "Country") +
  theme_minimal() +
  theme(legend.position="none")