Best visualization (small newsrooms) – year 2020
Winner: Danish scam
Organisation: Pointer (KRO-NCRV)
Credit: Peter Keizer, Wendy van der Waal, Marije Rooze, Jerry Vermanen, Wies van der Heyden
Jury’s comment: Dutch journalist and data researcher, Peter Keizer places readers in the driver’s seat on a journey into the murky world of identity theft. The colourful and bold layout is clean and simple and houses a detective story that analyzes emails and websites, screens companies and traces the Danish scammers’ employees via social media to the Philippines. Keizer uncovers 134 cases of identity theft and contacts some of the victims. “It’s my photo and name, but I didn’t know anything about it. I don’t like that at all. But I wonder how I can deal with those boys now,” complains one stooge. The whodunit format resonates with the public by showing how vulnerable all of us are to being scammed unwittingly. This piece might not be what we traditionally think of as data visualization but instead broadens the remit by transforming information into a visual context to tell a compelling story.
Organisation size: Small
Publication date: 12 Jul 2019
Project description: One day in 2019, we received an obvious spam email in which we were asked to publish a guest blog on our website. Normally we would delete this, but after a follow-up email we became curious on how this scam works. We decided to find out for ourselves. With the information in the email, we searched and found an elaborate network of two Danish scammers and at least 134 persons whose identities were stolen. We made an article in which we put you in the driver seat of our lead investigator.
Impact:After our first publication and visualisation, we made a TV broadcast 4 months after the fact. We translated our online production to TV, instead of making an online production from our programme. In the TV broadcast, we also filmed our investigator’s screen and tried to do everything from behind our laptop. During this second investigation, we discovered that the Danish guys improved their scam. They AI generated faces to fake reviews, contact persons and sell their content. So we made a second visualisation in which we explain how you can recognize this more sophisticated scam. We tried to contact as many victims as possible. Most of them didn’t know their identities were used for this scam.
Techniques/technologies:We didn’t want to tell this story in a familiar way: the most exciting part is discovering the answers step by step. So we searched for a way to translate a research on desktop to your mobile screen. We used OSINT techniques like reversed image search, Wayback Machine searching, Google Dorks, searching in chambers of commerce, digital forensics to find outgoing url’s, etc. to reveal the intricate and complicated network behind this scam. We also made our own database of persons whose identities were stolen. We needed to know how many people were involved, and if they knew anything about this scam. The most difficult person to find was Martyna Whittell, the fake identity of our emailer. She used photos of an existing person. We found the real ‘Martyna’ (her name is Mia) by geolocating her photos: we found a photo on a campus in Aalborg through a Starbuck coffee cup and a concert photo through the background of a Take That reunion tour. We eventually used face recognition in Yandex to find her friend on a group photo, and searching her friend list for a photo that looked like Mia.
The hardest part of this project: The hardest part of our research was finding Mia. We could find a lot of breadcrumbs online to reveal the scam(mers), but finding our main victim was difficult. Also, making a visualisation that works on mobile and puts you in the seat of our investigator was a real challenge. We could make a direct analogue with a desktop computer, because of the orientation of your screen. Forcing users to rotate their screens would be a step in which most people would back-out and quit. We found a way in which we made our own screens with illustrations. This also works great in this example, because we needed to anonymize almost everyone. We translated the story to English because this story is not only interesting for Dutch readers.
What can others learn from this project: The most important lesson is never to take anything for granted: a good investigative story can hide itself in an ordinary spam email you get every day. Also, making your own databases and being well-versed in digital research techniques is an essential part of modern investigative journalism. The translation from desktop to mobile was a successful, in our opinion. We found that a lot of readers scrolled to the end of our story.