#SRCCON2017
Session facilitators:
Ashley Wu @ashhwu - New York Magazine
Priya Krishnakumar @priyakkumar - Los Angeles Times
Sometimes it’s hard to see the data right before our eyes. In this session, we’ll talk about ways for people to find sources of inspiration for data-driven stories within communities they cover, even if no dataset currently exists.
We’ll talk about how to look for patterns in everyday occurrences to create structured datasets out of text, images, public statements and more, which can enrich and inform our storytelling. We’ll also look at some surprising data sets that already exist and discuss how to incorporate them into our own coverage and use them find new story ideas. Together, we’ll brainstorm data-driven stories inspired by what we find during our stay in Minneapolis, around SRCCON, or even the just in the room we’re in. We’ll workshop some of those ideas and expand the discussion to incorporate them into possible stories in our own communities. We’ll also talk about how to get the rest of your newsroom to think in a data-driven mindset while reporting, and leave with some story ideas to take back with us.
- Be able to collect your own data and pitch stories from it.
- Come away with one story idea to pitch
- Aggregating and displaying content in a functional way for users to explore. Example: Politico's White House logs
- Using the data to comment on our communities, society or government in some way. Example: Marshall Project's Pay to Stay jails
- Both! Example: Washington Post's Trump Charity Donations
- “It sure seems like Trump spends a lot of time at his own properties” vs. “Trump has spent 30% of his presidency at a Trump property.”
- “The single-rider line at Disneyland looks like it has a short wait time” vs. “The wait in the single rider line is 66 minutes shorter.”
- “I see the pizza emoji on Venmo a lot” vs. “The pizza emoji was used 17,470 times in one week”
- If Trump spent the last 7 weekends at Mar-a-Lago, how much does that cost Secret Service / taxpayers?
- Why is the pot industry only donating to Gavin Newsom's campaign for governor?
Even a tiny bit of structure can lead to higher reader engagement/involvement
- How will California's new laws affect my job/my health/my commute?
- The 351 People, Places and Things Donald Trump Has Insulted on Twitter: A Complete List
- Keep your scope relatively narrow scope.
- Track one metric at a time.
- Use pen and paper if it helps keep your thoughts organized
- Once you have some data, make some basic starter graphics -- they can be ugly!
- Malls
- When a mall dies, and there’s an empty space in the neighborhood, what's the effect on the surrounding neighborhood? Does crime go up?
- A ranking of the most walkable malls
- Collective distance of all the escalators in a mall
- Waste created by malls
- Fortune 500 companies
- Have diversity policies promised by Fortune 500 companies been implemented in the way they were promised? How has it affected the makeup of these companies?
- How consistent are PR campaigns around carbon emmissions versus actual results and actions of companies? Do certain companies get a lot of media coverage but actually have relatively low change?
- Food and Drink
- Areas where places do and don't deliver, compared to racial or socioeconomic data of that community
- How nasty is your ice?
- Metrics of restaurants that have opened in the last few months, and try to predict if they will last
- Restaurant names that change over time
- OSHA data, health and injury reports in restaurants
- Organic ingredients - are they local or not?
- Public Transportation
- Citations: figuring out the best time to not get cited if you don't pay for your ticket
- How many people take public transportation vs. how many people live in that city vs. population density
- Public transit deserts
- Events
- Marches and protests
- Pride parades, how corporate they have gotten over time
- Denied event permits - racial disparities, do certain people get denied more often? Is it higher in one place
- Police presence at events and police overtime - security costs across major American cities (Trump rallies, Black Lives Matter)
- Lakes
- Deaths around lakes, other human related illnesses related to lakes
- Who owns state lakes? Looking at satellite or GIS data, or matching it up with property data - so who owns what?
- How dirty are the lakes?
- How much lakefront property in Minnesota is available to the public?
- Honor system for fishing permitting? How honest are Minnesota fisherman?