Reminder: “Twitter Is Not America”

A summary of recent data from Pew provides the reminder that Twitter hardly represents the United States as a whole:

In the United States, Twitter users are statistically younger, wealthier, and more politically liberal than the general population. They are also substantially better educated, according to Pew: 42 percent of sampled users had a college degree, versus 31 percent for U.S. adults broadly. Forty-one percent reported an income of more than $75,000, too, another large difference from the country as a whole. They were far more likely (60 percent) to be Democrats or lean Democratic than to be Republicans or lean Republican (35 percent)…

First, Pew split up the Twitter users it surveyed into two groups: the top 10 percent most active users and the bottom 90 percent. Among that less-active group, the median user had tweeted twice total and had 19 followers. Most had never tweeted about politics, not even about Twitter CEO Jack Dorsey’s meeting with Donald Trump.

Then there were the top 10 percent most active users. This group was remarkably different; its members tweeted a median of 138 times a month, and 81 percent used Twitter more than once a day. These Twitter power users were much more likely to be women: 65 percent versus 48 percent for the less-active group. They were also more likely to tweet about politics, though there were not huge attitudinal differences between heavy and light users.

In fancier social science terms, this suggests what happens on Twitter is not generalizable to the rest of Americans. It may not reflect what people are actually talking about or debating. It may not reflect the full spectrum of possible opinions or represent those opinions in the proportions they are generally held throughout the entire country. This does not mean that is no value in examining what happens on Twitter, but the findings are limited more to the population that uses it.

In contrast, the larger proportion of Americans who are on Facebook might appear to suggest that Facebook is more representative of the American population. But, another issue might arise, one that could dog social media platforms for years to come: how much content and interaction is driven by power users versus the percent of users who have relatively dormant accounts. I assume leaders of platforms would prefer more users become power users but this may not happen. What happens to any social media platform that has strong bifurcations between power users and less active users? Is this sustainable? Facebook has a goal to connect more people but this is unlikely to happen with such disparities in use.

This is why discussing or confirming trends seen on social media platforms might require more evidence from other sources or longer periods of time to verify. Even what might appear as widespread trends in social media could be limited to certain portions of the population. We may know more about smaller patterns in society that were once harder to see but putting together the big picture may be trickier.

 

The United States in its second prolonged period of immigration?

Many know that the decades at the end of the nineteenth century and early twentieth century were a period of significant immigration to the United States. This is regularly taught in history classes and often celebrated. While it can be difficult to understand larger patterns as they are happening, a recent Pew report provides evidence that a second long immigration period is happening now in the United States:

Nearly 14% of the U.S. population was born in another country, numbering more than 44 million people in 2017, according to a Pew Research Center analysis of the U.S. Census Bureau’s American Community Survey.

Pew_19.01.31_ForeignBornShare_ImmigrantshareofUS_2

This was the highest share of foreign-born people in the United States since 1910, when immigrants accounted for 14.7% of the American population. The record share was 14.8% in 1890, when 9.2 million immigrants lived in the United States.

Whether the trend line goes up, down, or plateaus remains to be seen (and immigration is a controversial topic at the moment). Still, even if it dropped in the coming years, now would still be part of a longer trend that people and scholars will look back at.

Putting the figures in international context might prove helpful as well:

Even though the U.S. has more immigrants than any other country, the foreign-born share of its population is far from the highest in the world. In 2017, 25 countries and territories had higher shares of foreign-born people than the U.S., according to United Nations data

Worldwide, most people do not move across international borders. In all, only 3.4% of the world’s population lives in a country they were not born in, according to data from the UN. This share has ticked up over time, but marginally so: In 1990, 2.9% of the world’s population did not live in their country of birth.

A number of countries could claim to be a “nation of immigrants” – a common refrain in the United States – though how all of that came to be would certainly differ as would how the immigrants were and are understood.

The changing concept of TV ratings

Recent report from Netflix about the number of viewers for certain movies and TV shows raises questions about what ratings actually are in today’s world:

These numbers were presumably the flashiest numbers that Netflix had to offer, but, hot damn, they are flashy—even if they should be treated with much skepticism. For one thing, of Netflix’s 139 million global subscribers, only about 59 million are American, something to bear in mind when comparing Netflix’s figures with the strictly domestic ratings of most linear channels. Another sticking point: What constitutes “watching”? According to Netflix, the numbers reflect households where someone watched at least 70 percent of one episode—given the Netflix model, it seems likely that most people started with Episode 1—but this doesn’t tell us how many people stuck with it, or what the average rating for the season was, which is, again, an important metric for linear channels…

Ratings are not just a reflection of how many people are watching a TV show. They are not just a piece of data about something that has already happened. They are also a piece of information that changes what happens, by defining whether we think of something as a hit, which has a knock-on effect on how much attention gets paid to that show, not just by other prospective viewers, but by the media. (Think how much more has been written on You now that we know 40 million people may have watched it.)

Consider, for example, how something like last year’s reboot of Roseanne might have played out if it had been a Netflix series. It would have been covered like crazy before its premiere and then, in the absence of any information about its ratings at all, would have become, like, what? The Ranch? So much of the early frenzy surrounding Roseanne had to do with its enormous-for-our-era ratings, and what those ratings meant. By the same token, years ago I heard—and this is pure rumor and scuttlebutt I am sharing because it’s a fun thought exercise—that at that time Narcos was Netflix’s most popular series. Where is Narcos in the cultural conversation? How would that position have changed if it was widely known that, say, 15 million people watch its every season?

Multiple factors are at play here including the decline of network television, the rise of cable television and streaming services, the general secrecy Netflix has about its ratings, and how today we define cultural hits. The last one seems the most interesting to me as a cultural sociologist: in a fragmented media world, how do we know what is a genuine cultural moment or touchstone compared to being a small fad or a trend isolated to a small group? Ratings were once a way to do this as we could assume big numbers meant it mattered to a lot of people.

Additionally, we today want quicker news about new trends and patterns. A rating can only tell us so much. It depends how it was measured. How does the rating compare to other ratings? Perhaps most importantly, the rating cannot tell us a lot about the lasting cultural contributions of the show or movie. Some products with big ratings will not stand the test of time while others will. Do we think people will be discussing You and talking about its impact on society in 30 years? We need time to discuss, analyze, and process what each cultural product is about. Cultural narratives involving cultural products need time to develop.

Decades-long trend: complex suburbia

A 2018 review of what we learned about American suburbs ends with this:

It all added up to a portrait of suburbia as a landscape of dynamic cultural and structural change, not sleepy stasis.

I would suggest this is a change that has been happening for decades. Here are the first four features of a more complex suburbia that come to mind. They each go back quite a while:

  1. Different kinds of suburban communities. The prototypical suburban community looks like Riverside, Illinois or Levittown, New York, places primarily for commuters, consisting of single-family homes., and attracting middle to upper-class residents. These communities had a limited numbers of jobs and local businesses and men were expected to commute to the big city (via train or automobile). The problem with this view, common to find since any book on the history of the suburbs mentions these two bedroom suburbs, is that different kinds of suburbs have been around for at least a century. Different kinds of suburbs included: working-class suburbs, suburbs of non-white residents, industrial suburbs, and suburbs with various levels of density of housing and commercial or industrial property (including edge cities).
  2. The move of industry and jobs to the suburbs. Even as a good number of early suburbs were bedroom suburbs, the suburbs also proved attractive to industry because of cheap land, access to transportation, and the ability to pollute away from millions of residents in the big city. East St. Louis, Illinois or Gary, Indiana grew as industrial suburbs. After World War Two, the number of jobs grew in suburbs as businesses moved to the suburbs to be closer to workers (or perhaps closer to their CEOs) and suburban residents desired more goods and shopping options (shopping malls, big box stores, restaurants, etc.). By more recent years, the most common commute in the United States was suburb to suburb, not the supposedly typical suburb to big city commute.
  3. Changing suburban populations. While most early suburbs were white (notwithstanding the occasional community of non-white suburbanites who could not live in white suburbs), suburbs in recent decades have become home to an increasing number of non-white residents. Additionally, poorer residents have made their way to the suburbs in recent decades. These non-white and poorer populations may have hit a certain critical mass in recent years but the trends go back at least a few decades.
  4. Growing cultural and entertainment options in the suburbs. This trend is more recent than the first three but is still relatively common across metropolitan areas: suburbanites do not need to go into the big city for entertainment and cultural options. The suburbs feature a number of restaurants, museums, parks, music venues, festivals, and other options that make it easier for suburbanites to rarely need to go into the big city for a night out. Certain cultural options may still be richer in the big cities but more regular cultural options are now often found just a few suburbs over.

All of these suburban features may be coming together in new ways or presenting challenges to more suburbs that never thought they would change dramatically from their character at founding. Additionally, thinking about these intertwined suburban traits could help us move past seeing cities and suburbs in a strict dichotomy and instead view metropolitan regions as more cohesive wholes with similar interests and problems to address.

News story suggests 40% is “Almost Half”

A Bloomberg story looks at the rise in birth in the United States outside of marriage and has this headline:

Almost Half of U.S. Births Happen Outside Marriage, Signaling Cultural Shift

And then the story quickly gets to the data:

Forty percent of all births in the U.S. now occur outside of wedlock, up from 10 percent in 1970, according to an annual report released on Wednesday by the United Nations Population Fund (UNFPA), the largest international provider of sexual and reproductive health services. That number is even higher in the European Union.

Almost Half of U.S. Births Happen Outside Marriage, Signaling Cultural Shift

There is no doubt that this is significant trend over nearly 50 years. One expert sums this up toward the end of the story:

The traditional progression of Western life “has been reversed,” said John Santelli, a professor in population, family health and pediatrics at Columbia’s Mailman School of Public Health. “Cohabiting partners are having children before getting married. That’s a long-term trend across developing nations.”

Yet, the headline oversells the change. A move from 10% of births to 40% of births is large. But, is 40% nearly 50%? When I hear almost half, I would expect a number between 45% and 49.99%. Claiming 40% is nearly half is going a little too far.

I think the reading public would better served by either using the 40% figure or saying “Two-Fifths.” Or, perhaps the headline might speak to the 30% jump in nearly 50 years.

In the grand scheme of things, this is a minor issue. The rest of the story does a nice job presenting the data and discussing what is behind the change. But, this is a headline dominated age – you have to catch those eyes scrolling quickly on their phones – and this headline goes a bit too far.

Supercommuters up 15.4%, or 0.4 million, between 2005 and 2016

A small and rising number of Americans commute more than ninety minutes a day:

While super commuters still represent a small share of the overall workforce, their long commutes have become increasingly common over the past decade. In 2005, there were about 3.1 million super commuters, roughly 2.4 percent of all commuters. By 2016, that share had increased by 15.9 percent to 2.8 percent of all commuters, or about 4 million workers. In some parts of the country the problem is much worse; in Stockton, where James lives, 10 percent of commuters travel more than 90 minutes to work each day.

The rising number of super commuters underscores a general trend towards longer commutes. The share of commuters traveling 24 minutes or less to work each day has decreased to 55 percent of all commuters in 2016 from 59 percent in 2005. Meanwhile, the share of commuters traveling 25 minutes or more has increased to 45 percent in 2016, compared to 41 percent in 2005. The share of commuters traveling an hour or more to work each day increased 16.1 percent to 9.2 percent in 2016 from 7.9 percent in 2005.

I understand that this article is geared around showing differences in commuting over time. And the data can back that up: supercommuting is up and more Americans have longer commutes.

At the same time, this may be overselling the data:

  1. The changes over 11 years are relatively small. The article talks about percentage changes but the absolute numbers are small. This is the difference between supercommuting is up 15% versus saying it is up 0.4 million.
  2. Given that this data is based on samples of the US population, is a 4% change statistically significant? Is an increase from 2.4 million supercommuters to 2.8 supercommuters substantively significant?
  3. What are the trends between 2005 and 2016? Both of these measurement points are with a more robust economy. Driving was down after the housing bubble burst – was supercommuting affected by this? Is the trend line steady in an upward direction over the last 11 years or is it up and down?

From a broader view, this is not that much change. (There may still be shock value in reminding the public that 2.8% of all commuters are really willing to go far each day.)

Multiple measures and small trends: American birthrates down, births per woman up

A new Pew report explains this statistical oddity: the annual birthrate in the US is down but women are having more children.

How can fertility be down even as the number of women who are having children is going up? There are complex statistical reasons for this, but the main cause of this confusing discrepancy is the age at which women are having children. Women are having children later in life — the median age for having a first baby is 26 now, up from 23 in 1994 — and this delay causes annual birth rates to go down, even as the cumulative number of babies per woman has risen…

 

Another factor, Livingston said, is the drop in teen birth rates, with black women seeing the biggest drop in that category.

See the Pew report here. An additional part of the explanation is that there are multiple measures at play here. A Pew report from earlier in 2018 explains:

But aside from this debate, the question remains: Is this really a record low? The short answer is: It’s complicated.

That’s because there are different ways to measure fertility. Three of the most commonly used indicators of fertility are the general fertility rate (GFR); completed fertility; and the total fertility rate (TFR). All three reflect fertility behavior in slightly different ways – respectively, in terms of the annual rate at which women are presently having kids; the number of kids they ultimately have; or the hypothetical number they would likely have based on present fertility patterns.

None of these indicators is “right” or “wrong,” but each tells a different story about when fertility bottomed out.

Measurement matters and the different measures can fit different social and political views.

I wonder if part of the issue is also that there is a clear drop in births from the earlier era – roughly 1950 to 1970 which we often associate with Baby Boomers – but the last 3+ decades have been relatively flat. This plateau of recent decades means researchers and commentators may be more prone to jump on small changes in the data. Many people would love to predict the next big significant rise or fall in numbers but a significant change may not be there, particularly when looking at multiple measures.