One year, three elections in Spain

Category: Best visualization (small and large newsrooms)

Country/area: Spain

Organisation: eldiario.es

Organisation size: Big

Publication date: 28/04/2019

Credit: Raúl Sánchez, Pablo J. Álvarez, Héctor Figueroa, Gilberto López, Jorge Rodríguez, Ana Ordaz, Henar Álvarez

Project description:

In 2019, Spain public agenda was defined by political issues. The country lived 2 general, and 1 regional, local and european elections during this period. eldiario.es data team – 4 members –  did more than 60 publications based on data to explain:  the rise of the far right political party, the victory of social democrats, the fall of traditional conservative parties, the weaknesses of the electoral system or vote inequality by income level in maps, among others. This project integrates different visualization solutions to explain a complicated electoral (national, regional and local) and multi-party political system for all publics. 

Impact reached:

According to the Sociological Research Center (CIS), eldiario.es is the digital native media most read in Spain to get informed about political issues in Spain. Readers trust on eldiario.es to follow up the coverage related to the electoral process in terms of quality and reliability. According to our metrics, the outcome of the main visualizations generated around the electoral year accumulate in total more than 1M page views. Also, more than half million users has read the stories delivered behind the data. 

Moreover, many mainstream political talk shows on TV as Al Rojo Vivo in La Sexta TV, one of the biggest TV channels in Spain,   mentioned eldiario.es visualizations during the electoral period, that stands out our journalistic work and the relevance of the data. The information spread has also inspired other journalist and opinion leaders to write their own personal analysis of the political scene, for example: Ignacio Escolar (1 million followers) wrote an opinion about who poor people and rich people vote for and why using our data to understand than phenomena.

To make better reporting about the electoral process, the data journalist team at eldiario.es has focus on analyzing and storytelling the voting results in terms of gender, ideology, society behaviour, voting evolution or life standards as the main topics.  This figure shows that the society are interested not only on knowing the percentages but the narrative concerning voting behaviour and results.  

Social Media also played a significant role to impact due to many academics, professors, politicians and journalists has shared the content helping eldiario.es to loudspeaker the impact and get significant recognition. For example, José Fernandéz-Albertos, one of the most respect political analyst in Spain, shared our publication asking people to subscribe to the membership program of eldiario.es, because of the quality of our material. 

Techniques/technologies used:

For this project, we used Excel, R (tidyverse, dyplr and others), Open Refine, SPSS, Node and Python for data analysis and data binding. D3, React, Canvas Javascript, Illustrator, Mapbox GL, Tippecannoe, Datawrapper, Flourish, Scrollama y QGIS for data visualization, scrollytelling and maps. 

For example, we used Open Refine to clean a hundred thousand names of all municipality mayors in Spain’s democratic history to figure out that half of all councils have never had a mayoress. We analysed with R electoral results and income distribution from 34.000 voting precincts to explain how conservative parties are stronger in rich areas and how far-right party is growing faster in poor areas.

Our main maps and graphics were made with D3 combining Canvas with SVG and enhanced with React to improve loading and transition. To create voting precincts maps, we used QGIS and Tippecanoe to reduce the size of geographic files to optimize mobile navigation and Mapbox GL javascript library to map the results. 

The election application is served on Google Cloud Platform with Firebase and is composed of several technologies. For the backend we have a series of microservices in nodejs, both to extract the data and to serve them, additionally a microservice in python to combine two large csv and in the frontend we have React. 

What was the hardest part of this project?

Spanish electoral system is a multi-party proportional unlike other majoritarian electoral systems. This means that the results are not divided in two antagonical blocks. That created a huge first challenge: Our system has a multi-party proportional representation with many local and regional realities that must be pictured. For example: all the graphics and maps have to tell who is the winner, but also the second and third place parties that are important in the negotiations to choose the president.  We had to deal with more political parties than ever in Spain history, and most of them only participated in regional and local election. Some political parties only participated in one of 8,000 municipalities or one of the 17 regions.

This together with the range of our users ages that goes from 20 to +65 years a bigger challenge related with usability, interaction and comprehension issues. To solve that our little data team (two data journalists, three developers and a graphic designer) developed a multi-platform through desktop and mobile that showed the information hided behind the data. As a result, many visualizations has pop-ups showing additional information, or maps ar subdivided in categories to better understand the meaning of the data. 

Our project helped the audience to understand the behaviour of the spanish citizens in term of voting does not regard to a single issue. Despite the elections are the central thread of all visualizations, the data was not the same for each visualization delivered. That’s why our other challenge was to collect data and create more that 20 databases related with income, demography, age, gender, born place or historical voting. This was a work of more than 12 months that allow us to be ready to compare and tell stories with new focus to explain the electoral process. 

What can others learn from this project?

How to represent electoral results in multiparty political systems. 

Coding and technical tools to have data visualizations and analysis in real time. 

How to compare and explain a political transformation and patterns in a country or region with other issues such as gender, economics and other geographical and demographic data. We think our method could be extended and create an analysis that apply to whole Europe.

Methods to create collaborative work between sections of a newspaper. In this project we work with each one of the thematic sections of the newsroom to analyze how electoral results can affect all the edges of a country. 

Project links: