« When data meets politics » is a serie of eight data-driven stories based on different databases created by Wedodata from day 1 of Macron’s presidency in France. Parliamentary debates, vote on laws, Twitter messages, official diaries… All information concerning French elected representatives and the government is recorded. In 2019, two episodes have been published on LesJours.fr, a French online-only news website (six in 2018). They are devoted to the exploration of French political life through the prism of Wikipedia: one on the reputation of French elected representatives and the other on the publishing war of Wikipedians on these political
Since 2016, LesJours.fr has published 130 journalistic series on various topics : migrants, environnement, corruption, health, economic and political scandals… But this independant media – awarded by the Albert Londres prize, the French equivalent of the Pulitzer prize, in 2017 – hadn’t published before a data investigation and therefore it is a new ground for them and their subscribers. The audience of this “data serie” was one of the best among their 130 series, surely because it mixed the following 4 ingredients: the subject of politics ; new editorial angles thanks to the data ; “stories articles”, an innovative format inspired by Snapchat or Instagram and created for the occasion, ideal to read on mobile ; and visual articles offering datavisualizations, photos and GIFs.
The format of story proposed by a media directly on its site and not by forcing the reader to go on an external platform was very noticed by the French press which is looking for audience’s engagement.
On an international level, this project has been selected as a finalist for the 2019 “Online Journalism Awards” on the category“Excellence and Innovation in Visual Digital Storytelling, Small Newsroom”.
Most of the data sources that we query regularly are compiled by Python scripts that we have improved over time. In concrete terms, we use the following techniques: http request, page consultation automation with machine-controlled browsers, API queries when they exist.
This data is stored in distinct CSV files organized by a meta-database. Analysis, data mining, and angles seach for the stories were done through Tableau.
What was the hardest part of this project?
The hardest part of every journalistic investigation is to find the unexpected. What we learned by looking at French politics only through data is that it allowed us to get out of the “elements of language” written by political communicators and to provide concrete benchmarks to readers. This was the demonstration that one could interest readers in French politics other than through controversy and “snowclones”.
But for that, you have to look for data that is more distant from conventional open data. Of course Twitter, but also Wikipedia for these articles published in January 2019 which allowed us to show that the content of each page of French elected representativesis the place of a war of influence : we scrap all modifications and corrections made each day on MPs Wikipedia page to see if the pages were “vandalized” and by whomthanks to the totally open archives of the online encyclopedia : http://screenstory.wedodata.fr/lesjours/index.php?story=wikipedia2-english#1/no
Another challenge was to find the right way of writing a “story article”. It’s a whole other way of telling a story, because the texts must be short, dynamic, suitable for reading on a mobile with graphics. We tested a lot of ways before finding a solution that mixed writing on Google slides and oralizing texts as if we were preparing texts for the radio.
What can others learn from this project?
This project shows that data is a raw material that adapts to many web formats, that you have to be attentive to usage to see how journalism can seize practices from social networks to inform and that you don’t always need millions to innovate.