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Words and numbers in journalism: How to tell when your story needs data

Update: A more recent version of this material appears in my book, The Curious Journalist’s Guide To Data.

I’m not convinced that journalists are always aware when they should be thinking about numbers. Usually, by training and habit, they are thinking about words. But there are deep relationships between words and numbers in our everyday language, if you stop to think about them.

A quantity is an amount, something that can be compared, measured or counted — in short, a number. It’s an ancient idea, so ancient that it is deeply embedded in every human language. Words like “less” and “every” are obviously quantitative, but so are more complex concepts like “trend” and “significant.” Quantitative thinking starts with recognizing when someone is talking about quantities.

Consider this sentence from the article Anti-Intellectualism is Killing America which appeared in Psychology Today:

In a country where a sitting congressman told a crowd that evolution and the Big Bang are “lies straight from the pit of hell,” where the chairman of a Senate environmental panel brought a snowball into the chamber as evidence that climate change is a hoax, where almost one in three citizens can’t name the vice president, it is beyond dispute that critical thinking has been abandoned as a cultural value.

This is pure cultural critique, and it can be interpreted many different ways. To start with, I don’t know of standard and precise meanings for “critical thinking” and “cultural value.” We could also read this paragraph as a rant, an exaggeration for effect, or an account of the author’s personal experience. Maybe it’s art. But journalism is traditionally understood as “non-fiction,” and there is an empirical and quantitative claim at the heart of this language.

Continue reading Words and numbers in journalism: How to tell when your story needs data

Peace, Conflict, and Data

A talk I gave at the IPSI Bologna Symposium on conflict resolution. Slides here.

We might be able to do better at conflict resolution — making peace in violent conflicts — with the help of good data analysis. There have long been data sets about war and violent conflict at the state level, but we now have much more.

There are now extraordinarily detailed, open-source event data streams that can be used for violence prediction. Conflict “microdata” from social media and communications records can be used to visualize the divisions in society. I also suggest a long term program of conflict data collection to learn, over many cases, what works in conflict resolution and what doesn’t.

We’re really just at the beginning of all of this. There are huge issues around data collection, interpretation, privacy, security, and politics. But the potential is too great to ignore.

Update: two excellent resources have come to my attention in the days since I gave this talk (which is, of course, part of why I give talks.)

First, see the International Peace Institute’s paper on Big Data for Conflict Prevention. This paper was co-authored by Patrick Meier, who has been deeply involved in the crisis mapping work I mentioned in my talk.

But even more awesome, Erica Chenoweth has done exactly the sort of data-driven case-control study I was contemplating in my talk, and shown that non-violent political resistance succeeds twice as often as armed resistance. Her data set, the Nonviolent and Violent Campaigns and Outcomes (NAVCO) Data Project, also shows that non-violence is much more likely to lead to good democracies five years later, and that a movement that can recruit 10% of the population is almost guaranteed to succeed.

I highly recommend her talk.