Data Journalism

I've got a few qualms about using data in articles. Of course, data can add to the accuracy of any writing, but at the same time, data can take away from the story as well.

One major concern I have with using data in articles is that it is difficult to know how much data is too much data. The fine line is very blurred because on one end, you want to make sure you get all the information your audience may want but for some, what they want is too much for others. An example of where the line is most commonly blurred is in sports journalism. Sports fans want stats, stats on their favorite team. Or stats on their favorite player. Even stats on their favorite player compare to other players. But too many stats can take away from the story. If you're reading about how Steph Curry is a force to be reckoned with on the west coast, too many stats take away the human aspect of the story, making the subject more of a machine. The one way to alleviate this problem is to just write the story first and trim the fat of data and stats from the work.

Another gripe I have with using data is that it takes time to gather original data. With the field of journalism growing towards the digital and social media-reliant age, there's no time to waste when writing a story. Developing and releasing surveys, calculating stats, all of these things take time. Most likely, by the time the data is collected, the initial story is already out to the public and the data is only going to reinforce what is already known, losing relevance. The only way I can see this problem being addressed is if journalists stick to using data provided by government or private sector companies like the Bureau of Labor Statistics or PETA to deliver the statistics needed.

An example of a news source that does data right would be Vice News. Often in their articles, if data is needed, it is delivered sparingly - only used in important place where it is absolutely needed.