Room for Rent

2022

Country/area: Netherlands

Organisation: Argos, VPRO/HUMAN

Organisation size: Small

Publication date: 22/10/2021

Credit: Reinier Tromp, Saar Slegers

Biography: Reinier Tromp is a Dutch data journalist. He has a background in artificial intelligence. He also build the first Covid-dataset in the Netherlands that gave insight in the total amount of positive test that were conducted in the Netherlands.

Project description:

Anyone who rents a room anywhere in The Netherlands, quickly pays 500 euros per month for just about 10 square meters, sometimes even 1000,-. Square meters that are too expensive, because according to the rental law rooms belong to the social rental sector. A points system has been designed for this, which determines the maximum rent.
Argos built a scraper. We analyzed all rooms on Kamernet, the largest provider in the Netherlands. Many landlords appear to be flouting the law. We discovered that 8 of 10 rooms are (much) too expansive.

Impact reached:

This story has been picked up by more 100 news outlets in The Netherlands. Not only did almost every major newspaper and news website publish the news, but because the results were presented per city, many local media have written their own story from it.

RTL News, one of the largest broadcasters in The Netherlands, broadcasted a TV item on their 18.00 hours news program.

A tv documentary has also been made from it

Parliamentary questions have been asked to the minister of Home Affairs.

We made an English translation of our project, we will send this to your organisation via e-mail tomorrow. In case you have any question, you can e-mail us at r.tromp@vpro.nl

Techniques/technologies used:

The method I have chosen is to scrape all rental ads in the period from September 1 to October 11 from the largest room provider in the Netherlands: Kamernet. And then calculate the legal price of these rooms using the points system and compare it with the asking price.

For the scraper I have used the Scrapy framework and for the calculation I wrote a script in in python.
For visualisation, Flourish has been used.
Git and Github for version control and collaboration.
Code editor: Spyder.

What was the hardest part of this project?

The hardest part of this project was the combination of pure computer programming together with making a story for radio, tv and the website. Calculating the prices for each room was based on a fysical policy book that I have made computational, with many exceptions. For coders: that means a hell lot of ‘if, else statements’… But pure the numbers on itself don’t give a good story. Next to it, cases had to be found. Flesh and blood. So apart from coding I went to housing protests to record audio and find persons who were weighed down by the abuses on the housing market.

I think this story should be selected because it combinates hard numbers based on data together with intimate stories of common people who face the intimidation that can be caused by the lack of control on the Dutch housing market.

What can others learn from this project?

That evidence to proof large failures of the system can be hidden in data that is out in the open, if you ask the right questions. Protest against high rents were already ongoing in the Netherlands, but no other journalist had the idea to proof that this was even against the Dutch law. Our data investigation got the hard evidence that human rights were violated.