One result of this is extreme polarization on what should be more or less objective facts; for example, 41 percent of Americans believe human activity causes global warming, but the same number either say warming is due to a natural cycle (21 percent) or say there is no warming at all (20 percent). According to the Pew Research Center,60 public opinion about global warming is deeply segmented along political lines: “Democrats are far more likely than Republicans to say there is solid evidence that temperatures are rising (by a margin of 81% to 58%), and that human activity is the root cause (by 54% to 24%).” That does not mean Democrats are necessarily more pro-science. The scientific consensus, for example, is that GMO foods are not harmful to health, but a strong majority of Democrats think they are and are in favor of labeling them.61
Another result of constantly talking to the same people is that the members of a group tend to have shared opinions on most issues. Eclectic political positions become increasingly untenable in the face of a resolute herd, even one that is resolutely wrong. In fact, Democrats and Republicans do not even speak the same language anymore.62 Matthew Gentkzow and Jesse Shapiro, two economists who are leading scholars of the media, write about members of the US House of Representatives: “Democrats talk about ‘estate taxes,’ ‘undocumented workers’ and ‘tax breaks for the wealthy,’ while Republicans refer to ‘death taxes,’ ‘illegal aliens,’ and ‘tax reform.’ The 2010 Affordable Care Act was ‘comprehensive health reform’ to Democrats and a ‘Washington takeover of health care’ to Republicans.” It is now possible to predict the political affiliation of a congressman simply by listening to the words they use. Unsurprisingly, partisanship (defined as the ease with which an observer can infer a congressperson’s party from a single sentence) has exploded in recent decades. Between 1873 to the early 1990s, it did not change, increasing from 54 percent to just 55 percent during this period. But it increased sharply after 1990; by the 110th session of Congress (2007–2009) it was 83 percent.
This convergence of opinions and vocabulary is precisely why access to Facebook data was so useful to Cambridge Analytica and to political campaigns in the UK and the US. Since most Massachusetts Democrats, for example, have more or less the same views across a wide range of questions and use the same words, it takes just some snippets of our opinions to predict our politics, how we should be targeted, and what types of stories we are likely to like or dislike. And, of course, once real people embrace this cardboard cutout predictability, it becomes that much easier to invent characters, create fake profiles, and inject them into an online conversation.63
This insularity also creates an opportunity for skilled political entrepreneurs to present themselves very differently to very different people. During the run-up to the 2014 election for prime minister that he won in a landslide, Narendra Modi in India managed to be at many rallies at the same time by using full-scale, three-dimensional holograms that many voters took to be real. He also managed to be at more than one place in ideological terms. To the generation of globally connected ambitious young urban Indians, he was the embodiment of political modernization (emphasizing innovation, venture capital, and a slick pro-business attitude, and so on); the new entrants into the expanding middle class saw him as the one most likely to uphold their vision of nationalism rooted in Hindu tradition; for the economically threatened upper castes, he was the rampart against the (largely imagined) growing influence of Muslims and lower castes. If members of these groups had met together and each had been asked to describe “their” Modi, their answers would probably have been largely unrecognizable to the others. But the networks in which these three groups operated were sufficiently separate that there was no need for internal consistency.
THE NEW PUBLIC SPACE?
The sharp segmentation of the electorate goes much deeper than just policy disagreements. Americans of different political hues have started to positively hate each other. In 1960, roughly 5 percent of Republicans and Democrats reported they would “[feel] ‘displeased’ if their son or daughter married outside their political party.” By 2010, nearly 50 percent of Republicans and over 30 percent of Democrats “felt somewhat or very unhappy at the prospect of inter-party marriage.” In 1960, 33 percent of Democrats and Republicans thought an average member from their own party was intelligent, compared to 27 percent who had the same view about someone from the other side. In 2008, those numbers were 62 percent and 14 percent!64
What explains this polarization? One of the most important changes since the early 1990s, when partisanship started its sharp increase, is the expansion of the internet and the explosion of social media. As of January 2019, Facebook had 2.27 billion monthly active users globally, while Twitter had 326 million.65 In September 2014, more than 58 percent of the US adult population and 71 percent of the US online population used Facebook.66 (That does not include us, so everything we have to say about these networks is second hand.)
Originally, virtual social networks were billed as the new public place, the new way to connect, and hence something that should have reduced homophily. In principle, they provided an opportunity to connect with distant people with whom we shared some specific interest, say in Bollywood movies, Bach cantatas, or raising babies. These people might not have been like us in other ways, offering us a more eclectic choice of friends than what would result from mere physical proximity. They would have had almost nothing to do with each other, so to the extent we would get to exchange views about things other than the precise topic that brought us together, we would all be exposed to a variety of opinions. Indeed, on Facebook, 99.91 percent of the two billion people on it belong to the “giant component,” meaning that almost everyone is everyone else’s friend of a friend of a friend.67 There are only about 4.7 “degrees of separation” (the number of “nodes” you have to cross) between any two people in the giant component. This implies that in principle we could easily be exposed to pretty much everyone’s views as they travel through the social network.
Nevertheless, virtual social networks have mostly failed to integrate their users on divisive issues. A study of 2.2 million politically engaged users on Twitter (defined as those who followed at least one account associated with a candidate for the US House during the 2012 election period) in the United States finds that while there are roughly ninety million network links among these users, 84 percent of the followers of conservative users are other conservatives, and 69 percent of the followers of liberal users are liberal.68
Facebook and Twitter function as echo chambers. Democrats pass on information produced by Democratic candidates, and Republicans do the same for Republicans. Eighty-six percent of first retweets of tweets by Democratic candidates come from liberal voters. The corresponding number for Republicans is an amazing 98 percent. Taking into account retweets, liberals get 92 percent of their messages from liberal sources, and conservatives get 93 percent of their messages from conservative sources. Strikingly, this is not just true of political tweets; for these politically engaged people, the exposure is just as skewed for nonpolitical tweets. Apparently, even to chat about fly fishing on Twitter, people prefer to connect with a fellow liberal or conservative. The virtual community that social networks have created is at best a fragmented public space.
But is there anything specific about social media that causes this polarization? The political strategies to divide the population and plant fake news were invented long before Facebook. Newspapers have always been highly partisan, and political mud-slinging was the bread and butter of the print media in colonial America, and continued into the early days of the American Republic (in the musical Hamilton, it is the threat of scurrilous press coverage that forces Hamilton to own up to his affair). The “Republican noise machine” was perfected on cable TV and talk radio in the 1990s, as David Brock powerfully documents in his book bearing that title.69
An even more powerful demonstration of just how destructive old media can be comes from the Rwandan genocide. Before and during the g
enocide, Radio Télévision Libre des Mille Collines (RTLM) called for the extermination of the Tutsis, whom they called “cockroaches,” justified it as self-defense, and talked about the supposed atrocities committed by the Rwandan Patriotic Front (or RPF, the Tutsi militia). Villages that RTLM reached experienced significantly more killings than villages it did not due to the mountains blocking radio wave transmissions. Altogether, RTLM propaganda is estimated to be responsible for 10 percent of the violence, or about fifty thousand Tutsi deaths.70
Gentzkow and Shapiro computed an “isolation index” for the year 2009 (which in some ways feels like a lifetime ago, but the internet was already quite vibrant) both for online and offline news. This was defined as the difference in the share of news items with a conservative slant a conservative was exposed to and the share of news items with a conservative slant a liberal was exposed to. What they found seemed to suggest polarization was happening offline just as much as it was online. The average conservative’s exposure to conservative views online was 60.6 percent of their total news consumption, the equivalent of a person who gets all their news from usatoday.com. The average liberal’s exposure to conservative positions was 53.1 percent, at the same level as cnn.com. The isolation index for the internet (the difference between the two) was therefore just 7.5 percentage points, a little bit higher than the isolation index for broadcast news and cable television news, but lower than that for national newspapers. And it was much lower than the segregation of in-person contact. It was already true in 2009 that conservatives had mostly conservative friends, and the opposite for liberals. The isolation index is low because, in their data, both conservative and liberal users visited mostly “centrist” sites, and those most likely to visit extremist sites (like Breitbart) also visited many others, including those with opposite perspectives.71
While it is true that polarization has increased among online users, it has also increased in other spheres of life. Indeed, while polarization has increased in all demographic groups since 1996, it increased the most among those sixty-five or older, who are the least likely to be on the internet, and increased the least among the youngest people (those aged eighteen to thirty-nine).72 Polarization has also increased in traditional news media. A textual analysis of the content of cable news showed that since 2004 the language used by Fox News has become increasingly slanted to the right, while MSNBC has moved to the left.73 The audiences have also diverged. Until 2008, Fox News had a stable share of about 60 percent Republicans among its viewers. This share increased to 70 percent between 2008 and 2012. Over the years, Fox News became increasingly conservative, which attracted more conservative voters, who in turn pushed it to be even more conservative. This has begun to affect voting patterns. We know this because in some counties in the United States Fox News shows up at a less accessible part of the dial, for purely accidental reasons, and therefore people are less likely to tune in to it.74 In those counties people are also less prone to vote for conservatives.
So what is it that changed? In Congress, according to Gentzkow and Shapiro, the turning point seems to have been 1994, the year of Newt Gingrich’s takeover of the Republican Party and his “contract with America.”75 This was also the first year political consultants played a key role in designing and testing messages, which is something that as social scientists interested in the design and testing of innovations, including in messaging, we find rather disturbing.
NETWORKING NOT WORKING
Even if political polarization did not wait for the internet, it is hard to be entirely sanguine about the effects of the virtual social networks and the internet on our policy preferences, and the ways they are expressed. For one, we don’t really know the counterfactual; what would the world be like without these innovations? Comparing those with and without access to the internet, like the young and the old, does not answer this question, for many obvious and less obvious reasons. In particular, the internet is often the place where rumors get manufactured and circulated before they make their way to Fox News, where older people get to hear them. Perhaps younger people are less moved by these rumors because they know the internet is full of errors and exaggerations and can correct for them, whereas older people, used to trusting the booming authority of television anchors, are more gullible.
There are other concerns as well. The first is that the circulation of news on social media is killing the production of reliable news and analysis. Producing fake news is of course very cheap and very rewarding economically since, unconstrained by reality, it is easy to serve to your readership exactly what they want to read. But if you don’t want to make things up, you can also just copy it from elsewhere. A study found that 55 percent of the content diffused by news sites and media in France is almost entirely cut and pasted, but the source is only mentioned in less than 5 percent of the cases.76 If a piece of news produced by a team of journalists is immediately cut and pasted onto many other sites, how does the original source get rewarded for its production? It is no surprise that the number of journalists in the United States has plummeted in the last few years, going from nearly 57,000 in 2007 to almost 33,000 in 2015.77 There are both fewer journalists in total and fewer journalists per newspaper. The economic model that sustained journalism as a location for “public space” (and correct information) is collapsing. Without access to proper facts, it is easier to indulge in nonsense.
The second concern is that the internet allows for endless repetition. The problem with echo chambers is not just that we are only exposed to ideas we like; we are also exposed to them again and again and again, endlessly, throughout the day. The fake users used to “boost” stories on Facebook plus the real persons paid to “like” content accentuate the natural tendency for some messages to be repeated and acquire a life of their own. The endless repetition whips people into a frenzy (much like the way political demonstrations use repeated chants), making it harder for them to stop and check the stories.
And even if the truth eventually gets out, the many repetitions of a falsehood can raise the salience of a divisive issue and harden extremist views. We remember only the endless talk about Mexicans (who we never trusted in any case) and not the fact that first-generation immigrants, legal or otherwise, are actually less likely to be criminals than native-born Americans.78 This of course creates a very strong reason to flood the markets with alternative facts. A hundred and fifteen pro-Trump fake news stories that circulated before the 2016 presidential election were viewed thirty million times (pro-Clinton fake news stories also existed, but they were viewed only eight million times).79
The third is that the crabbed language of internet communication (which Twitter takes to an extreme) encourages directness and abbreviation, contributing to the erosion of the norms of civic discourse. As a result, Twitter has turned into a lab for trying out the latest nasty pitch. Political entrepreneurs are happy to plant their wildest claims on Twitter and watch them play out, with an eye to whether they have gone too far. If it seems to be working, at least among the targeted group (as measured by retweets or likes, for example), they add it to the pack of potential strategies for the future.
Fourth, there is automatic customization. In 2001, when Sunstein was writing about echo chambers, he was worried about the opportunity users have to choose the news they consume. Increasingly, there is no need to choose. Sophisticated algorithms use machine-learning prediction techniques to try to figure out what we might like based on who we are, what we have searched before, etc. The objective, quite explicitly, is to get people what they like so they spend more time on it.
Facebook came under pressure for the algorithm it used to push stories to users, and in 2018 it promised to reprioritize its feeds, putting posts from friends and family ahead of media content. But you do not need to be on Facebook for this to happen. On Esther’s Google home page on July 2, 2018, there was one article from the Atlantic, “The Trade Deficit Is China’s Problem”; Paul Krugman’s latest op-ed in the New York Times; one arti
cle from the New York Times on millennial socialists; one article on the soccer World Cup; one article from the Boston Globe on Lawrence Bacow, the new president of Harvard; one article on Simone Veil’s burial; a Huffington Post article on Senator Susan Collins’s view on the choice of the latest Supreme Court justice; and the unavoidable article about the Pixel Watch. There were only two stories she was not obviously interested in: one about a criminal escaping a French prison by helicopter (which turned out to be lots of fun) and a piece on Fox News about Busy Philipps fighting with Delta Air Lines for rebooking her and her child on different flights. That last piece was her entire exposure to right-wing media for the day. Such customization is ubiquitous. Even the National Public Radio app (“NPR One” to the cognoscenti) calls itself “Pandora for Public Radio,” referring to the app that gives you the music you like based on what you have listened to in the past. Within the echo chamber for liberal ideas that is NPR, an algorithm will filter for the user exactly what the user likely will want to hear.
This matters because when users actively choose what they are reading, they are at least conscious of what they are doing. They may prefer to read articles from familiar sources, but be sophisticated enough to acknowledge their own biases reflected in those sources. An unusual experiment in South Korea demonstrated that this kind of sophistication is very real. From February to November 2016, two young Koreans created an app offering users access to curated articles from the press on topical issues and regularly asked them their opinions on the articles and on the issues themselves. At first, all users received a randomly selected article about each issue. After a number of rounds, some randomly selected users got to choose the news sources from which they received their articles, while others continued to receive randomly selected articles. The experiment yielded three important results. First, users did respond to what they read: they updated their views in the direction of what was being presented to them. Second, as expected, those given the option chose articles generally aligned with their partisan preferences. Third, however, at the end of the experiment, those who got to choose their articles had updated their preferences more than those who did not, and they had generally updated toward the center! This is the opposite of the echo chamber effect. On balance, the option to choose slanted material made users less partisan. The reason is they understood exactly how biased the source they chose was, and partly undid the bias, while being receptive to the information; whereas with randomly assigned stories, users did not recognize the bias and therefore remained skeptical about the content, not changing their opinion much.80
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