Tag Archives: google

Marriage is going down, so what does Kanye West have to do with it?

The marriage rate has fallen almost continuously for more than half a century, from a sky-high 90 per 1,000 unmarried women in 1950 (meaning almost 1 in 10 single women got married that year) to a bare 31 per 1,000 in 2011. Splashdown appears imminent.

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Sources: 1940-1960; 1970-2011.

Social scientists understand that there is a combination of demographic, economic, policy, and cultural factors involved. These include the aging population, men’s declining fortunes, the incarceration of millions of poor men, the rise of secular ideology and the sexual revolution.

Often, however, cultural influence is left to what you might call residual interpretation. Proving that culture affects demographic trends is difficult. Instead, people consider how demographic, economic and policy factors play their roles, and then attribute what’s left of the trend to culture.

Recently, the National Center for Family and Marriage Research at Bowling Green University reported the marriage rate for each state and D.C., ranging from 61 marriages per 1,000 unmarried women in Utah down to 19 per 1,000 in Washington, D.C. and 20 in Rhode Island. To explain the pattern using normal demographic practices, I gathered some other data about states from the Census Bureau: The percent of the population over 65, percent female, percent with a BA or higher education, population density, per capita income and race/ethnic composition. With that information – using a regression – I can guess the marriage rate to within 3.1 points on average. This is what the regression looks like, showing what happens when I start with age and sex composition, add income and education, and then add race/ethnicity:

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In statistical terms (R2), my simple model explains 73 percent of the variation in marriage rates, which is pretty good. Before I would use the marriage rate as an indicator of something like “culture,” then, I would say most of what’s going on reflects larger demographic and economic patterns that we more or less understand. The differences that remain, however, still might be the result of cultural, religious, or attitudinal factors that are harder to assess. (I stress this is not about low Black marriage rates: note the population percentage Black has no effect once the other factors are controlled.)

Culture, meet big data

What about big data, the billions of bits of information people leave strewn around wherever they go? Marketers and government spying agencies make most of the headlines, but social scientists, too, are scraping up millions of words and turning them into analyzable numbers, so they can tell you things like:

One of the easiest sources to use for this kind of thing is the Google Correlate tool, which finds the search terms whose frequency most closely follows a specified pattern. I entered the marriage rate for each state, shown on the map on the left, with darker green indicating higher marriage rates. Google Correlate tells me which searches track this variation: which searches are most popular in Utah, least popular in D.C., and so on. (I actually trimmed the Utah rate to it wouldn’t be such an outlier, from 61 down to 57, just above the next highest). It turns out the most correlated search is for “rolls recipe,” which is correlated with the marriage rate at .85 on a scale of -1 to 1.

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But since my interest is in the decline of marriage, I multiplied the marriage rate by -1 and tried again (so now darker green indicates a lower marriage rate). The answer, overwhelmingly: Kanye West. (Experts at finding any website anywhere will know that he’s a never-married proud father-to-be with co-parent Kim Kardashian.)

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That correlation between the inverse of the 2011 marriage rate and “kanye west my beautiful dark twisted fantasy” (his last album) is .81. Further, Google produces the top 100 most correlated searches, and of those, no fewer than 28 were about Kanye West (such as “kanye west new album,” “devil in a new dress lyrics” and “air yeezys”). Another 16 were other hip-hop searches, including some about Jay Z and Lil Wayne. Other apparent themes include mafia-related entertainment (“sopranos episode,” “pacino movies,” “corleone”) Sex and the City, and shopping at Marshalls.

Does this tell us more than the simple demographic analysis I did above? When I put the top Kanye search into my model, it has the strongest effect, and the variance explained jumps to 81 percent. The model now can predict the marriage rate to within 2.5 points on average.  It’s a very good predictor, and it’s not just reflecting simple demographics like age, gender and race. Whether Kanye is in the analysis or not, Black population percentage has no effect on this prediction. Here is the regression, with new parts in red:

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Explanations

So, I dredged all the search data in the world for something correlated with marriage rates, and found something. But what does it mean? Two cautionary stories are revealing. Forecasting guru Nate Silver has a good description of how noise looks like signal. For example, with the tens of thousands of economic statistics available to build a forecasting model, finding a pattern after the fact is deceptively easy. But it usually doesn’t work for predicting future economic trends.

Another caution comes from genomic studies. In a study of, say, cancer genetics, statisticians may conduct millions of tests for the association between any genetic variant and the occurrence of cancer. With the typical definition of “statistical significance” – which tolerates a 5 percent random chance of being wrong – that means they’d find hundreds of thousands of bogus “significant” associations. So good scientists set their significance threshold for such studies much tighter, more like.00005 percent than 5 percent. That way they are sure to only blow the whistle on genes if the chances of being wrong are vanishingly small.

So, this is a suggestive game of Big-Data Craps, not real research. It’s meant to provoke a little. I hope we’ll think creatively about new kinds of data we can use. Also, I want to generate ideas about cultural explanations for demographic trends. It should be at least as useful as some pundit simply declaring, for example, that gay marriage is killing real marriage. (“As the cause of gay marriage has pressed forward,” wrote Ross Douthat, “the social link between marriage and childbearing has indeed weakened faster than before.” That theory has about as much going for it as one linking the decline of marriage to the rise of high fructose corn syrup or the explosion of red cards in World Cup soccer.)

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Kanye’s fantasy

With those caveats, here are three possible explanations for the finding:

  1. Google, by trawling through millions of search term patterns, has come up with a random bit of noise that just happened to catch my attention. There’s nothing there, really.
  2. The hip-hop Google search is capturing a more finely-grained demographic pattern than I did with my simple Census numbers. So what matters for marriage is not just things like the percentage female, education levels and racial composition of the population, but the presence of particular combinations of these demographic groups. Hip hop’s audience is notoriously difficult to define — it’s featured on top-five radio stations in markets such as San Francisco and Los Angeles as well as Detroit and Atlanta — but it’s certainly not as simple as age, gender, and race
  3. Hip-hop actually is weakening marriage in America. People who listen to Kanye West and other hip-hop music are taken in by the music’s consumerist individualism and shun marriage, with its staid image of tradition, conformity and restraint. As a result, they are less likely to get married than the people Googling “rolls recipe.”

I lean toward explanation #2. Explanation #3 might have something to it. As the philosopher xkcd wrote, “correlation does not imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there.’” But I wouldn’t draw that conclusion without a lot more evidence, including doing some comparisons to other cultural factors, like other kinds of music or religious patterns. Since I have no expertise in hip hop (post 1989), I would be glad to hear from people who know about it for realz.

Addendum: Here’s a scattergram showing the correlations between some of the variables in the regression. In each cell there’s a dot for every state plus DC. The Kanye variable is scaled (by Google) to have a mean of 0 and standard deviation of 1 (click to enlarge).

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What are we becoming a nation of now?

In Jonathan Haidt’s TED talk, “How common threats can make common political ground,” he mentions an influential New York Times article about how people with college degrees are more likely to get and stay married compared with those without college degrees.

At about 15:20 in the talk, Haidt says: “We are becoming a nation of just two classes.”

And I got to thinking about that phrase, “become a nation of…” It puts the reader at the moment of a transition from an assumed past to a specified future. A Google Books search reveals that we have become a nation of many things over the years:

1805: Becoming a nation of free men.

1815: becoming a nation of drunkards.

1822: becoming a nation of castes.

1840: becoming a nation of bull-dogs.

1856: becoming a nation of music lovers in the legitimate sense of the term.

1905: becoming a nation of dreamers, and then, in the next sentence, becoming a nation of money lovers and materialists.

1905: becoming a nation of physicians or even of lawyers.

1944:  fast becoming a nation of neurotics.

1953: becoming a nation of coffee drinkers instead of one of tea drinkers, like England.

1969: becoming a nation of two societies— one white and one black— separate and unequal. (from this awesome issue of Ebony:)

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1977: becoming a nation of the elderly.

1985: Becoming a Nation of Readers.

1987: becoming a NATION OF ILLITERATES.

1988: becoming a nation of hamburger stands, and, in the same sentence, becoming a nation of management consultants, doctors, software designers, and international bankers.

1989: Becoming a Nation of Burger Flippers?

2008: becoming a nation of joiners.

2008: becoming a nation of orthorexics (people with an unhealthy obsession with healthy eating)

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Do people working work in working families?

It’s not that “working families” don’t exist, it’s just the way most people use this term it doesn’t mean anything.

Search Google images for “working families,” and you’ll find images like this:

4f4a9a28-ff28-4bc7-88e5-f0df4522b2dbAnd that’s pretty much the way the term is used: every family is a working family.

To hear the White House talk, you have to wonder whether there are people who aren’t in families. I’ve complained about this before, Obama’s tendency to say things like, “This reform is good for families; it’s good for businesses; it’s good for the entire economy.” As if “families” covers all people.

Specifically, if you Google search the White House website‘s press office directory, which is where the speeches live, like this, you get 457 results, such as this transcript of remarks by Michelle Obama at a “Corporate Voices for Working Families” event. The equivalent search for “working people” yields a paltry 108 hits (many of them Obama speeches at campaign events, which include false-positives, like him making the ridiculous claim that Americans are the “hardest working people on Earth.”) If you search the entire Googleverse for “working families” you get about 318 million hits, versus just just 7 million for “working people” (less than the 10 million that turns up for “Kardashians,” whatever that means.)

You would never know that 33 million Americans live alone – comprising 27% of all households. And 50 million people, or one out of every 6 people, lives in what the Census Bureau defines as a “non-family household,” or a household in which the householder has no relatives (some of those people may be cohabitors, however). The rise of this phenomenon was ably described by Eric Klinenberg in Going Solo: The Extraordinary Rise and Surprising Appeal of Living Alone.

This is partly a complaint about cheap rhetoric, but it’s also about the assumption that families are primary social units when it comes to things like policy and economics, and about the false universality of “middle class” (which is made up of “working families”) in reference to anyone (in a family with anyone) with a job.

Here’s one visualization, from a Google ngrams search of millions of books. The blue line is use of the phrase “working people” as a fraction of references to “people,” while the red line is use of the phrase “working families” as a fraction of references to “families.” It shows, I think, that “working” is coming to define families, not people.

CaptureThis isn’t all bad. Families matter, and part of the attention to “working families” (or Families That Work) is driven by important problems of work-family conflict, unequal care work burdens, and so on. But ultimately these are problems because they affect people (some of whom are in families). When we treat families as the primary unit of analysis, we mask the divisions within families – the conflicts of interest and exploitation, the violence and abuse, and the ephemeral nature of many family relationships and commitments – and we contribute to the marginalization of people who aren’t in, or don’t have, families.  And those members of the No Family community need our attention, too.

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What do Jews Google on Christmas?

I don’t know. But I do know what Google searches are geographically correlated with searches for “Hanukkah,” and it includes “Chinese food.”

Here are the maps:

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The map looks close to the Jewish population map from the 2010 U.S. Religion Census (a private outfit).

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Here are the top-100 most Hanukkah-like searches, in the obvious categories: Religious/cultural, Howard Stern, Food, Travel and People.

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Merry Christmas.

 

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Signs of the times, mass shooting edition

Couple ngram associations. See them here.

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Obama Top Chef Romney Founding Fathers

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If you don’t collect data on individual web users, and don’t have a big-data budget, you can still learn a lot about how people voted in this presidential election from some creative probing of the Google Correlate database. The power of the tool is in uploading your own data (such as vote tallies) to see what searches mirror your target pattern.

For example, the map on the left is what I uploaded: the ratio of Obama votes to Romney votes in each state, as of Thursday morning. The map on the right, from Google, is the relative frequency of searches for “top chef.” The two patterns have a correlation of .88 on a scale of 0 to 1.

cohen_topchef.pngMaybe it’s a complete coincidence that Michelle Obama appeared on a Top Chef program earlier this year. But out of the 100 Google searches that most closely match that vote pattern, eight are aboutTop Chef. Others on the list include “spliff” (never heard of it), “mos def” and various reggae artists, as well as “itchiness.”

On the other hand, searches for “founding fathers quotes” follow the Romney/Obama ratio just as closely:

cohen_foundingfathers.pngMost of the searches on the top-100 Romney-state list (all correlated about the same .84) are about simple, non-obscene pleasures, such as “clean jokes,” “clean funny jokes,” “funny commercials”; and home-schooling materials, like “flag clipart,” “in god we still trust,” and “printable scrapbook.” After the kids are in bed, though, someone is Googling “hot cheerleader,” before quickly toggling back over to “sean hannity” when he hears mom coming up the stairs.

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Have Obama haters lost traction?

Maybe it’s because Donald Trump isn’t really a true hero to anti-socialist, anti-Muslim, racist Americans.

For whatever reason, there has been a real slump in the number of people typing “obama gun” (will he take our guns away?), “obama muslim” (the idea used to run at about 20%), “obama socialist” (the republic “hangs in the balance“), and “obama citizen” (thank you, Snopes) into the Google search box since the 2008 election.

Here’s the Google trend (and the search link):

We don’t know how much these fears, versus other concerns, will affect votes against him this year, although there have been some good efforts to track the effects of anti-Black racism on his vote tally.

Naturally, not everyone who Googles these things believes the underlying stories or myths. But it seems likely they either believe them, are considering them, heard someone repeat them, or are arguing with someone who believes them, etc. So I’m guessing – just guessing – that these trends track those beliefs.

But maybe four years of Obama as an actual president has softened up the hard-line hatred in some quarters. What do you think?

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