By Cecilia Campbell

Founder and journalism professor Gabriel Kahn joined forces with a PhD student in engineering and set about creating a tool whereby journalists can generate hyper local stories from publicly available, but previously inaccessible, data. The result: 114 weekly neighbourhood newsletters on everything from crime to public health, housing and traffic. And one stat to prove the value of hyper local: The open rate is north of 90 percent.

Kahn, a USC Annenberg School of Journalism of professor and Publisher & Editor at Crosstown in Los Angeles, shared his case during our World News Media Congress in Copenhagen, as part of our topic Breaking Data, i.e. how public data can be used to create valuable local content.

“I have found that being at a university is a wonderful place to innovate around news,” Kahn said. “I discovered this when I started meeting engineers at my university, because I realised that the engineers love to solve hard problems, and I was like, ‘Hey, I’m a journalist – I’ve got lots of hard problems. Why don’t you solve them?’ ”

The starting point: Scalable stories from public data

Kahn’s basic idea was to use data and automation to bring down the costs of covering local communities and increase engagement. His base is Los Angeles, but the same is true of many US cities: they publish troves of data, tracking quality of life issues including public safety, complaint calls from residents, building permits, parking tickets and traffic accidents.

What if it were possible to make this public, but mostly inaccessible, data available to journalists to a. surface stories on hyper local level and b. distribute them to readers on an equally granular basis. In other words: produce hyper local relevant content in a financially scalable way.

“One of the most important crises in America is, I feel, the evaporation of local news. What follows is grim; fewer people voting, less civic engagement and so on. The issue is there is no sustainable business model for local news. If we could bring down the cost, that would be equivalent of raising the revenue. So we tried to do that with data,” said Kahn. Crosstown was born.

The constituent parts: Data, dashboards and a newsletter platform

The data. In Los Angeles, the authorities publish 15 different data sets on their website on a daily, weekly or monthly basis. This is data about crime, arrests, housing, construction, traffic, citizen complaints, potholes, garbage, graffiti, home values, parking, business licenses, restaurant inspections and more.

A very useful aspect of this data is that each row of it has a latitude/longitude, in other words it is as granular as it can be in terms of geography. Crosstown uses those coordinates to tell stories at the neighbourhood level – and there are 114 of them just in Los Angeles.

The data dashboard. In order for journalists – in the first iteration that was just Kahn and another journalism professor – to access and use the data, the USC engineering student built a data dashboard.

“The data is very difficult to access – basically it’s publicly available but not publicly accessible. You need a PhD in data science in order to make it accessible. And once you get into this data, you realise that it tells the same stories that local news has been telling forever. If you can unlock it, you have a thousand stories that you can tell at any one time, and you can tell them at the local level.”

​The dashboard turns every journalist in the newsroom into a data journalist, because what it allows them to do is to ask questions of the data in a very simple way. You can take millions and millions of rows of data and find a pattern in them.

The newsletter platform. Remained the issue of getting the right stories to the right readers, what Gabriel Kahn refers to as “the last mile problem.”

The solution was to build a platform that allows Kahn and his colleague to write newsletters and populate them with hyper local data.

In other words, they write one newsletter but automatically deliver 114 unique ones, one for each neighbourhood. The newsletter platform also includes a library of custom data visualisations which journalists can use.

The platform includes custom data visualisations to match the data set types.

The result: ‘We contextualise news and we hyperlocalise news’

Each data set can generate a number of different stories depending on how you slice and dice it. Journalists can ask any question of the data, thereby uncovering lots of stories without having to do any sort of big mathematical operation. The answers appear right away. “​​We often find that other news organisations in Los Angeles are following us because we have this data before they do. We know how to read it.”

Crosstown’s work brings context to the city’s daily news. Thanks to being able to access and query the underlying data, it’s possible to challenge public perception of e g an increase in crime, by looking at whether isolated events in the news are in fact part of a pattern or not.

There is a lot of talk in the US news industry about news deserts in rural parts of the country. The fact is, they actually exist in the middle of Los Angeles. Thanks to the data dashboard, the Crosstown team can now examine how what is happening in the city impacts equity.

“We can essentially pull apart the city and we can really act as advocates for those who are underserved and underrepresented,” Kahn said.

He gave an example from another city where the Crosstown platform is used, Chicago.

Chicago has a service which allows citizens to call up and lodge complaints about city services, “a wonderful source of data,” according to Kahn. He asked the dashboard to look at complaints from people who hadn’t had their garbage picked up, on a weekly basis during the period January 2023–April 2024.

The graph (below) shows that there’s been 400–500 complaints every month. What stuck out was a huge spike in November, where the complaints tripled. “And I’m thinking, was there a strike among the garbage workers or something like that?

Kahn decided to look at the data in a different way, by neighbourhood. Chicago has 77 neighbourhoods and in the graph below you can see that two of them account for almost a majority of the complaints. “So now I’ve located the story and I can tell it to the people in that neighbourhood and tell them they are the ones losing out here.”

No marginal cost and opportunity for monetisation

The Crosstown dashboard has brought down the cost involved in asking a question of the data, turning it into a few seconds. And the newsletter platform means the model incurs no marginal cost for producing 2 or even 200 newsletters. In other words: the newsroom can produce and distribute more and more relevant content (because it is hyperlocal) at a lower cost.

And it doesn’t have to be in newsletter form – which perhaps is not the optimal delivery if you want to reach e g younger readers. What the platform does is generate a URL which is then scraped into the newsletter template. So the content could be delivered as a text message or a WhatsApp message.

Crosstown is still a non-profit organisation (although that will change), but Kahn sees opportunities for monetisation in that it would be possible to sell advertising to local businesses on neighbourhood level.

The Crosstown platform is in use in newsrooms in three US cities; Los Angeles, Chicago and Raleigh, North Carolina. The plan is to scale up the solutions to other newsrooms and cities. We’d also like to experiment with doing this in different languages so that in American cities we can reach people in Chinese and Spanish and other languages that don’t get the same kind of quality or quantity of news,” Kahn said.

Useful links and contact information

The Congress presentation of the Crosstown case on data journalism can be downloaded here.
Crosstown’s website is here
Gabriel Kahn can be reached at this email address:

This post was originally published on our Innovate Local site.

The post Hyper local journalism: How Crosstown built a platform for neighbourhood newsletters appeared first on WAN-IFRA.