The Hybrid Media System

by Andrew Chadwick

  That said, we should not mistake Trump’s amateur social media language for interactive deliberation. There is very little evidence that Trump, or Clinton for that matter, engaged in direct conversations with their Twitter and Facebook followers. Trump was much more likely to retweet members of the public, so the argument might be made that he was indirectly engaging with his supporters. But an analysis from the Pew Research Center reveals that these types of retweets took two main forms: Trump retweeted congratulatory messages from well-wishers and messages that were critical of his opponents. A good example was Trump’s retweeting of tweets from ordinary members of the public that referred to the Fox News anchor, Megyn Kelly, as a “bimbo” (Pew Research Center, 2016b: 21). We also know that Trump did not post all of his own tweets: often he left that job to his digital campaign manager, Brad Parscale, who had a database of 400 “template tweets” that he used to fire off tweet storms on a minute-by-minute basis to coincide with Trump’s media appearances (Green & Issenberg, 2016). While deprofessionalization may have been in evidence, so too was a reprofessionalization, of sorts.

  Trump may have used social media to present himself as an amateur, but he also used it to portray himself as a showbiz celebrity. By 2016, journalists had become used to staid and restrained tweets from politicians. In constant amazement at Trump’s gall, they lapped it up. Trump’s targets were often from the world of entertainment in which he moved, such as Meryl Streep, whom he described as being “overrated” following her denouncement of him at the Golden Globes ceremony, at which she received a lifetime achievement award (Izadi & Wang, 2017). Trump’s authenticity therefore rested upon a double movement: he was at once the ordinary guy and the billionaire who moved among, and interacted with, entertainment celebrities. Both of these characteristics, fused in his Twitter stream, helped with his goal of being presented, not as a career politician, but as an outsider hell-bent on going to Washington to “drain the swamp” of its wasteful bureaucracy, just as Republican and former Hollywood actor Ronald Reagan had promised in 1980.

  Trump also tweeted about what he was watching on live television, particularly if it was the conservative channel Fox News. These were not random acts. They were messages designed to create solidarity with the conservative activists and reporters who he assumed would be watching along with him or who, later in the day, might be using social media to discuss the issues raised on a show. A good example is a Trump tweet that exclaimed that those who burn the American flag should be jailed or have their citizenship rescinded. Moments before the message, Fox News’ Fox and Friends had carried a story about the burning of a flag on the campus of Hampshire College in Massachusetts (Hess, 2017). Trump was the first dual-screening candidate. In itself, this is a reflection of how seriously he took Twitter as a medium for setting the mainstream news agenda.

  Trump’s transgressive tweeting thus helped him in several decisive ways, though very few of these derived from his use of Twitter in isolation. Twitter enabled him to establish himself early on in the Republican primaries as one of the front runners in an unusually large field of seventeen candidates. It has become a commonplace of U.S. election studies that in order to gain “earned” (i.e., journalistic, not bought) media coverage during the early stages of the race, a candidate requires two things: favorable poll ratings and a demonstrable ability to raise money (Lawrence & Boydstun, 2016). But in Trump’s case, because his established celebrity television persona had already created a substantial Twitter following, his candidacy was already news. As soon as he announced his run in June 2015, he started to receive neutral or favorable coverage from mainstream news outlets, in plentiful quantities (Patterson, 2016). This radically reduced his campaign’s need for paid advertising. Across eight major news outlets (CBS, Fox, the Los Angeles Times, NBC, the New York Times, USA Today, the Wall Street Journal, and the Washington Post) for the pre-primary period January 1–December 31, 2015, Trump received an estimated $55 million of ad-equivalent neutral or favorable coverage. The New York Times provided $16 million worth of this equivalent coverage, an amount that exceeded Trump’s entire ad spending during the pre-primary period. And this earned media came despite Trump’s poor showing in the early opinion polls and his neglect of campaign fundraising during the primaries (Patterson, 2016).

  Once the primaries were underway, Trump’s earned media advantage over his Republican rivals widened still further. During the all-important month of February 2016 —the buildup to Super Tuesday, when thirteen states held their primaries—Trump spent just $10 million on advertising. This contrasted with the $82 million spent by Jeb Bush and the $55 million spent by Marco Rubio in that month. Even Democratic outsider candidate Bernie Sanders spent almost three times as much on advertising as Trump during this month (Confessore & Yourish, 2016). According to data gathered by the New York Times from media analytics platform mediaQuant, which analyzes online news, broadcast news, print news, blogs, forums, and Twitter, by March 2016 Trump had secured an estimated $1.9 billion of ad-equivalent earned coverage—six times more than Ted Cruz, almost ten times more than Jeb Bush and Marco Rubio, and, tellingly, more than double Hillary Clinton’s total. MediaQuant is a business and does not release the precise details of the sources for its index. We know, for example, that it includes Reddit and Twitter advertising equivalence metrics among its social media sources but not equivalence metrics for Facebook (Bialik, 2016). Still, what matters here is not so much the absolute accuracy of the index, but its usefulness for revealing the differences between the 2016 candidates. By the November election day, Trump had earned $4.96 billion of ad-equivalent coverage, while Clinton trailed at $3.24 billion. Trump outperformed Clinton across all media types, with particularly large margins for online news sources, blogs and forums, and an extraordinary advantage of 142 percent for Twitter. Overall, Trump earned more than three and a half times more coverage than Obama had earned during the 2012 race. This is all the more significant given that a sitting president, as Obama was in 2012, can always rely on large volumes of earned coverage (Harris, 2016).

  DRIVING COVERAGE TO THE NOMINATION

  What explains the elite media coverage that, in turn, enabled Trump to gain momentum and move to the front of the crowded Republican primary so quickly? Based on a content analysis of mainstream sources during the pre-primary coverage, which showed the extent of Trump’s free media coverage, political communication scholar Thomas Patterson argued that traditional news values explained this puzzle. Journalists, he suggests, were “behaving in their normal way,” by conveying to their audiences a novel and at times sensational Trump insurgency. Trump, Patterson says, “exploited their lust for riveting stories” (Patterson, 2016).

  But is this account complete? Patterson’s analysis excluded social media entirely. Yet it was Twitter that forged the link between Trump’s prior celebrity capital and journalists’ fascination with his political ambitions. Trump saw Twitter as a means of intervening in the political information cycles of the campaign to boost his earned media coverage. Also important to his approach was directly inspiring—and, in part, feeding off—a growing army of conservative online activists, who gravitated to right-wing online news sites such as Breitbart. Founded in 2007, by 2016 Breitbart had made it into the top fifty most popular websites in the United States. It had more than 2.3 million Facebook followers, and attracted 18 million homepage visitors a month during the campaign (Kreiss, 2017). A post-election automated keyword analysis by Yochai Benkler and colleagues of over 1.25 million news stories revealed that there were surprising similarities between the most prominent themes (immigration, Clinton’s character, jobs) of both Trump’s speeches and Breitbart’s news articles and the most prominent themes professional media used to report on the campaign (Benkler, et al., 2017). Disentangling whether it was Trump’s direct influence, or the right-wing news network’s indirect influence, that shaped professional media coverage is impossible with Benkler and colleagues’ data. But the key point here is that both
are likely to have played a role. Trump’s inflammatory tweets, rallies, and press conferences were always likely to be news. Yet social media sharing by Breitbart readers, made manifest in the form of visible metrics of engagement on Facebook and Twitter, further incentivized journalists to report on the controversy and the enthusiasm generated by Trump’s tweets, rallies, and press conferences. It was all news.

  A further point here is a contextual one about the changing structure of attention online. Since the latter part of the first decade of the 2000s, social media have decisively reshaped the incentive structures for online news. Social sharing optimization (SSO) has come to replace search engine optimization (SEO) (Karpf, 2016a: 93–122). This, in turn, is changing how attention to politically useful information is distributed around the media systems of the advanced democracies. The earliest model for driving attention was banner advertising. This was followed by a rush to use Google’s AdWords platform to secure placement against user searches. Soon after Google’s ascendancy in the advertising market, new digital news providers emerged, like Demand Media, which owned so-called content farms (like eHow and Cracked), designed to attract Google search users. Demand appeared to have mastered this SEO approach, but then social media platforms came along with a different model. As users flocked to Facebook and Twitter, it soon became clear that many individuals saw these as destinations not only for consuming news content, but also for sharing news in their interpersonal online social networks. By 2015, 63 percent of Americans with a Facebook or Twitter account said that they turned to these sites for news. Given that, by 2015, 62 percent of the U.S. adult population used Facebook and 20 percent used Twitter (Duggan, 2015), these were important shifts.

  SEO staggered on for some time as the organizing logic of online news, but by the mid-2010s it had been eclipsed by the logic of social sharing. New online news organizations like Buzzfeed and Vox were specifically designed to have social sharing “baked in,” not least because they announced their news on Facebook and Twitter at the same time as on their websites. Attention to news is now much less reliant on Google and much more reliant on the machine learning algorithms that distribute attention on social media platforms. And, while we cannot know the full details of these algorithms because they are commercial secrets, what we do know is that timing and engagement matter. Posts that receive high levels of user engagement in the form of shares, likes, comments, and retweets over a short period of time are more likely to show up in users’ news feeds (Bucher, 2012, 2018). This changed context, with its new audience expectations, was ripe for a candidate like Trump, who wanted to master the now-integrated temporal rhythms of professional news media and social media sharing.

  With this contextual shift in mind, what can we say about the success or otherwise of Trump’s social media strategy? Evidence comes from Chris Wells and colleagues’ study of the factors that drove news media attention to Trump during the primaries (Wells, et al., 2016a; see also Wells, et al., 2016b). Wells and his team built a large-scale, longitudinal data set covering an unusually wide range of sources that they gathered during the period from Trump’s announcement in June 2015 to the date of his primary victory on May 4, 2016. They wanted to see if there were any identifiable causal relationships between Trump’s Twitter activity, campaign events such as debates, interviews, and rallies, the growth over time of his Republican delegate count (as he steadily notched up primary victories), and the amount of mainstream media coverage he received.

  To enable this research design to work, Wells and his team needed the right data and the right method—not an easy task given the complexity of a presidential campaign. For each day during the eleven-month primary campaign, they tracked Trump’s delegate count, which is published by the Republican Party shortly after each primary or caucus. They gathered a one percent sample of all retweets of Trump’s tweets from Twitter and they logged the timing of the twelve official Republican primary debates. From Trumpshow.info, a website that aggregated all of Trump’s rally and media appearances during the campaign, they added data on events of three kinds: staged public events, such as campaign rallies; planned media events, such as interviews and press conferences; and what they termed “unscheduled media appearances,” which captured Trump’s unusual habit of personally calling in, uninvited, in the middle of television and radio talk shows.4 Using the Nexis news database (a global archive of all newspaper content), Wells’s team counted how many news stories mentioning Trump appeared daily in the New York Times, the Washington Post, USA Today, and on the Associated Press newswire service. Finally, to capture the huge quantity of material that newspapers now publish solely online, they also counted mentions in blogs managed by the New York Times and the Washington Post.

  While not a perfect data set—it contained no material from Facebook or local newspapers, nor from the popular news and commentary site Reddit, which was unexpectedly important during the 2016 campaign (Chadwick & Stromer-Galley, 2016)—Wells and his team went a long way toward capturing the data that matter for exploring interactions between campaign spectacle, social media, and broadcast and newspaper coverage. They had time-series data, which meant they could use two particularly appropriate statistical methods—Granger causality and autoregression. These allow researchers to apply statistical controls to identify the temporal direction of causality; in other words, they enable us to see whether Event A at Time 1 actually played a statistically significant role in shaping Event B at Time 2. The big question here was: Did Trump’s tweets lead to greater news coverage, or was it other factors, such as his staged media appearances?

  The findings were clear. Increases in the volume of retweets of Trump’s tweets led to increases in news articles and blog posts. Things did not work the other way around. In other words, there was no evidence to suggest that increases in retweets of Trump’s tweets were caused by increases in the number of news articles and blog posts being published in the press. The findings also showed that Trump was more likely to post tweets during periods when his news and blog coverage was relatively quiet, confirming the theory that he used Twitter to stoke the fires of coverage.

  Yet, in a confirmation of the real space-internet-television nexus, Trump also benefited from the traditional staged media events of the campaign, such as press conferences, rally coverage, and set-piece interviews. The data show that professional media quickly learned to cover Trump’s press conferences and to invite him to interviews, and these events would be more likely to be covered in subsequent news stories (though not in news organization blogs). Trump’s habit of calling in unannounced to radio and television talk shows also had an influence on the amount of news articles and blog posts, but only before the primary elections began, although arguably this was the period when such interventions were more crucial for establishing momentum. The televised primary debates were also important for driving increases in both news articles and news organization blogs. This is testimony to the disturbing power of Trump’s often outrageous remarks during these events. The final nail in the coffin of the argument that the press were simply doing their usual job by recording Trump’s increasing electoral popularity is that there was no statistical relationship between his delegate count and the amount of coverage he received (Wells, et al., 2016a). In other words, professional media did not seem particularly interested in framing their reports of Trump in terms of his growing support.

  Trump’s insurgent hybrid media strategy worked. It was a combination of his Twitter use, the volume of retweets by his Twitter followers, and staged media events such as press conferences, interviews, and candidate debates, as well as his direct interventions in broadcast news shows, that enabled him to gain the publicity he required from elite media organizations. This was not a process of disintermediation. Contrary to much of the popular commentary during the campaign, Trump did not use social media to “bypass” professional media; he used social media to influence professional media. This was not disintermediation; it was intermediation.
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br />   Trump’s Data Campaign and the Switch to Facebook Advertising

  Focusing solely on Trump’s use of television and social media might give the impression that he did not develop a data-driven ground campaign. This would be misleading, though the reasons why this is the case require explanation.

  Since 2004, the meaning of the term “ground campaign” has been redefined by a new generation of campaign personnel recruited to develop data-intensive strategies. This has involved the integration of broadcast-era “war room” professionalism, online fundraising, data science, field organizing, and the mobilization of large armies of volunteer campaign workers operating at the precinct level. Following the 2004 election, this combination of data, analytics, and the ground war evolved into the campaign norm for both the Democrats and the Republicans, albeit with different levels of intensity given the Democrats’ comparative advantage in 2008 and 2012 (see chapter 6 herein; Hersh, 2015; Kreiss, 2012, 2016; Nielsen, 2012).

  Despite the growth of online campaigning, broadcast-era logics of top-down presentational professionalism and tight control of campaign messaging integrate surprisingly well with this new approach (see chapter 6). For the Democrats in particular, discipline and calibration were central to the turn toward data and analytics. This involved campaign elites’ increasing use of experimental data science methods to interrogate large-scale aggregations of behavioral information from public voter records, off-the-shelf marketing databases, and digital media environments, with the aim of organizing and mobilizing key segments of the electorate to vote and to publicly and privately share their voting preference with others (Chadwick & Stromer-Galley, 2016: 284–285). Meanwhile, the Republicans’ 2012 defeat also jolted the GOP to increase investment in their digital infrastructure to keep pace with the Democrats (Kreiss, 2016: 168–203; Vogel & Samuelsohn, 2016). The analytics turn has produced new and surprising sources of organizational power inside both major parties. Digital media elites have embedded their expertise and operating norms, and these differ from those prevalent among staff who worked to perfect campaign media strategies during the broadcast era. How did the 2016 Trump campaign measure up against this context?