The Clark Medal is one of the most prestigious awards in all of academia, awarded to the “American economist under the age of forty who is judged to have made the most significant contribution to economic thought and knowledge.” (Names you might know among previous winners: Paul Krugman, Milton Friedman, Joseph Stiglitz, Steven Levitt, and Larry Summers.) This year’s honor went to Matthew Gentzkow of the University of Chicago’s Booth School of Business. Gentzkow is a pioneer in the field of media economics; his work, often co-authored with Chicago Booth’s Jesse Shapiro, takes advantage of previously unavailable data on audience, content, and media impact. Austan Goolsbee, also a Chicago Booth professor, commented on Gentzkow’s work in The New York Times:
“Before the Internet and advances in computing power, this couldn’t be done,” Mr. Goolsbee said. “You couldn’t analyze the data and you wouldn’t have had the ambition to try.”
Some of Gentzkow’s most talked-about research has been on bias in news sources — he’s written papers around measuring slant, whether readers consume diverse or confirmatory news, and whether there is a demand for biased news in the market. He’s looked at the impacts of television on children and on voting behavior, and he’s has studied online advertising.
Going forward, Gentzkow said he’s interested in looking at more international media — he’s focused on finding a comprehensive data set for global media content. He’s also excited about the potential for data created by geocoding and cellphones, as well as studying media impact on the individual level — maybe even with electrodes. We talked about the cost of information gathering, the demand for quality news, and the obstacles to gathering data; here’s our lightly edited conversation.
The challenge is trying to keep up, keep close enough to the frontier, keep learning new things, keep up with all these smart graduate students who are getting their PhDs and know a lot more than I do. Try to keep producing new research. It’s challenging, but certainly the data and the technology are going to keep getting better, and that makes it exciting.
I never worked in business — I didn’t do consulting or investment banking. Some of the things people traditionally work on, I didn’t have exposure to. Newspapers and TV and the Internet were things I felt like, as a consumer, I had some intuition about, thought about, found myself asking questions about. It was a good fit for me to work on something that had already piqued my curiosity.
And a third thing is how similar sorts of things play out in different countries around the world. Whether the U.S. media is a little bit conservative or a little bit liberal, that’s sort of important. But what’s happening in Russia, in China, in the Middle East, what happened in the Soviet Union, in communist countries — in those sorts of settings, there’s an order of magnitude bigger impact in some ways.
Now, doing that in practice is a little harder. Jesse [Shapiro] and I several years ago had a project where we were trying to aggregate news content from lots of different countries, partly with some help from Google News, and the computational challenges, the challenges of getting everything into a form where it was clean enough that you could do something with it, proved to be pretty hard. We ended up putting that project on the back burner because we couldn’t quite get it all to come together.
Somebody just showed me a website1 which is not primarily academic, where they actually have a very large number of sites around the world. They’re scraping them and categorizing them and backing out from them; automated measures of what events are happening — where, when, mapping them. It all sounded very exciting.
But in terms of text, I think in the digital space, pretty much everybody’s competing with everybody, so it makes sense to think of that as one market, whether it’s ABC.com or NYTimes.com or NPR.org. Whatever traditional media you’re coming from, once you’re putting content online, you’re competing in the same marketplace. Newspapers in the 19th century, TV in the 1950s, daily print newspapers in the U.S. in the mid-2000s — that’s something different.
There is a theme running through this work: that the differences across media (in the sense of medium) are smaller than people often imagine. A lot of the underlying economics is the same online as it was for print newspapers and TV, and as it was in the 19th century. I think that’s part of the lesson that comes out of all of this — that maybe, things don’t change quite as much as we think.
The purpose of the paper was very simple: Let’s go look at some data on the way people actually consume news online and see to what extent that’s true. Conclusion: not nearly as much as you might think.
If you ask why not, the answer is because the Internet is not all that different from any other medium. The key thing driving low segregation online is that most people get most of their news from a very small number of sites. They get their news from CNN.com or Yahoo.com, NYTimes.com, Fox News — a huge share of news consumption is a small number of big sites that are very much in the middle of the spectrum in terms of their audiences.
Why is that true? Why haven’t we instead seen something a little more like the scenario Cass Sunstein was talking about, where everybody reads their own niche site and there are thousands of different niches and each person is in one of them? Because it remains true that the fixed costs of producing good news are still really high. It’s easy to put up a website, but to produce original reporting news content is still really expensive. Creating a website like CNN.com that covers everything that’s going on and that people trust and believe in is hard, is expensive.
So you end up with, just like in lots of other media markets, a small number of firms control a large share of the market. Those firms that invest all that money in quality are not going to do that and then cater to the neo-Nazi vegetarian tiny little corner of the market. They’re going to position themselves in the center to appeal to a wide audience.
The economics that drove the finding in that paper, I think, are the same economics that explain why we see what we do in TV and why we see what we do in print newspapers. The details are different, the cost structure is different, but basically the production of news remains not actually all that different. That shapes in a big way the outcomes that we see.
The Internet has dramatically changed the technology for delivering information to people, and it’s also pretty dramatically changed the extent of competition and filtering and interpreting information. But it really hasn’t changed all that much the production of news. If we want to learn what’s happening in Afghanistan, pretty much somebody has to go to Afghanistan and put their lives at risk and take photographs and interview people.
Those things have changed some — yes, there’s crowdsourcing, people upload videos from their phone. And yes, lazy reporters can just sit at home and do research on Google, where they don’t actually have to go down and sit in a city council meeting. But I would say relative to changes in other parts of the business, the way reporting has changed is much smaller. I think producing good news stories remains something that’s very costly, requires a lot of skill, a lot of talent. That remains the scarce resource. That explains why the Internet isn’t quite so different as we might have thought.
I am more optimistic than some people about it. I don’t really buy the view that we train consumers to care about quality or not care about quality. I think the desire of people to know what is going on in the world from a source that they trust, that they believe is accurate, is a feature of humanity that’s been there for a long time. People in the Roman Empire cared a lot about getting the news, people in Medieval Europe cared a lot about getting the news, people in the 1920s cared a lot about getting the news, people today care a lot about getting the news.
What we’re picking up are decisions like: We have to call these people either undocumented workers or illegal aliens. Both of those terms are loaded, both have strong political connotations, we have to pick one or the other. People might debate this, but in my view there’s no such thing as the objective, correct term. Which decision you make will put you either to the left or the right, but it doesn’t make you better or worse or more or less accurate.
Saying that newspaper slant is driven by the readers doesn’t mean that catering to the readers is making newspapers worse or more biased or less accurate or lower quality. It just says: These differences we see, that some sound way to the left and some sound way to the right, are shaped by making the decisions that will appeal most to those readers.
There’s a separate question that we don’t take up in that paper which is: How does catering to readers affect quality? For example, maybe really all that people want to read about is celebrity gossip and scandals and local crime, and media end up covering those things to the exclusion of political debates or something that you think might have valuable social effect. Does catering to consumers make media more lowbrow, highbrow?
I think local crime is actually pretty important; political scandals are an important part of politics. Judging what news content is good for society and what news content is bad for society is a little bit of a tricky business. But I think it’s still a really interesting question.
For you, is there a dataset out there — maybe it exists, maybe it doesn’t, maybe you know where it is, maybe you don’t — but is there something, if it was quantifiable, that you’d want as your next dataset?
I think things at the individual level give you more insight into how people are reacting. Ideally, the hypothetical dataset is to look inside everybody’s head and see their beliefs and how they’re thinking about things. So maybe we can put electrodes in peoples’ brains and come up with a way to measure that directly.
Another thing that’s out there is all this geocoded data coming from the fact that everybody’s cellphone now tells you where everybody is every minute of the day. I don’t know what I’m going to do with it, but that’s going to be a huge area of research going forward.