Who remembers sitting in your [insert preferred mathematics class here] thinking, “When in the name of Merlin’s beard am I ever going to use this absurd theorem in real life? This feels like a gigantic waste of time.”
There was many an afternoon when that thought went through my head, which may explain why I chose a less numerically minded career path.
Here’s the rub:
The closer I look at everything we do here at AirPR (and everything PR pros do in general), the more I realize just how intertwined math is in our day-to-day work. From time management to data visualizations that allow audiences to extract meaning from numbers, math is everywhere.
PR measurement guru Shonali Burke sums it up nicely: “If you’re managing a client’s budget, you’re doing math. If you’re using data points to pitch a story, you’re doing math. If you’re managing a research project which comprises surveys, you’re doing math. If you’re running your own PR business, you’re absolutely doing math.
“When measuring PR, even if your metrics are primarily output metrics, you’re doing math,” she adds. “What else would you call counting all those impressions, hits, and followers? I think many [PR] pros think ‘differential calculus’ or other complicated functions when they hear ‘math.’ However, regular math? Everyone does it without even knowing it, so it’s time to stop being frightened of it!”
We couldn’t have said it better ourselves, Shonali.
To boost your computational confidence, we tapped a few mathematically minded folks to help uncover five hidden ways PR pros are using math.
1. Probability theory and classification
To see these two principles in action, look at the intrinsic ranking methods used to identify priorities and hierarchies before, during and after PR campaigns. Not every PR activity gets the same amount of attention or time dedicated to it.
By weighting outputs, ranking outlets and making explicit choices to use some words or messages more than others, you’re enacting the underlying principles of probability theory and classification.
2. Multiplication and other arithmetical functions
Ever find yourself calculating the percentage change in a PR metric over time? What about looking at shifts in company share price? All these activities require the application of basic arithmetic.
Google Analytics advocate Adam Singer says: “Determining ROI of a campaign or understanding the statistical significance of a test are table stakes skills for communications pros. Even if your area of focus doesn’t involve these things today, it likely will in the near future. This is a good thing, as the more we can hone our craft to be as much science as art, the larger our budgets will get.”
3. Calculus and geometry
Visual content is everywhere, and non-number-minded folks are likely to point to imagery as more of their jam. It might come as a surprise to visually driven individuals that all visuals (e.g., graphs and pie charts) are tapping calculus and geometry to tell their stories.
Visuals make it easier to extract meaning from numbers while providing indicators of rates of change, growth in profit, etc. Don’t ever say geometry never did anything for you.
AirPR Software Engineer and self-proclaimed math enthusiast Ryan Rapp astutely pointed out the applications of statistics in PR. “Statistics answers the question of how many of X do we need before results are reliable and perhaps repeatable.”
He goes on to say, “When you look at a lot of articles, you can find labels and apply designations to subsets of placements, like this 20 percent of outlets are generating leads, that 80 percent are perpetuating a specific message, etc.”
Though complicated to pronounce, this one is easy to understand. Combinatorics is used to calculate degrees of separation and maximum reach within audiences according to how interconnected those groups are.
Think about the network effect. Combinatorics gives you a sense of how information can theoretically spread across different groups. When you engage influencers or target specific journalists, you’re calling on the power of combinatorics to help you realize the greatest reach and impact of your work.
“Doing math” doesn’t necessarily mean busting out a protractor, figuring out the statistical significance of a subset of data points, or living in Excel-land. It simply means acknowledging the quantitative underpinnings of PR’s often-qualitative work.
Everyone does math, so let’s embrace the power of the discipline-even if only to embolden and empower the number-crunching prowess that lurks deep down within every PR pro.
Say it with me now: “I am a PR pro, and I can do math.”
But this research paper is less a piece of objective scientific inquiry and more the work of corporate-commissioned data tricksters — a rancid pile of pro-Facebook propaganda that derives and frames its conclusions with the sole purpose of making Facebook look good.
This isn’t science. It’s PR.
And because press releases — even ones with funky algebra and annotations — are never allowed to reflect poorly on a company, it’s not hard to predict what this Facebook-commissioned study, carried out by Facebook researchers, concluded when investigating whether Facebook’s algorithms contribute to political polarization.
The paper concluded that the News Feed algorithm — which helps determine the stories users are most likely to see on Facebook — had but a minuscule effect on limiting users’ exposure to viewpoints different from their own. The real perpetrator of political echo chambers on Facebook, the researchers found, were users themselves, because they fail to click on stories they disagree with and their friends are predominantly like-minded politically. The study essentially asserts that if you’re a liberal and when you log into Facebook all you see are stories that preach to your bleeding heart choir, it’s not Facebook’s fault — it’s your own for being too closed-minded and for not getting along with conservatives.
If true, that conclusion holds great significance. More and more, algorithms are responsible for the media we consume — whether it’s the stories served up by Facebook or the films Netflix recommends — and the products we buy, as companies like Amazon and Google strive to know what products users want before users know it themselves. From Mark Zuckerberg’s high-minded praise of journalistic institutions to the company’s grand ambitions to directly host content supplied by newspapers and magazines, Facebook endeavors to become the predominant platform and filter for news — and by “news” I don’t just mean what the guy who sat next to you ten years ago in Chemistry class had your breakfast. And therefore it’s crucial to keep Facebook accountable for providing factual and balanced streams of information, just as if it were the New York Times or NPR
A cursory glance at this study, along with many of the aggregated news stories that summarized it, suggest that in this respect at least Facebook is a responsible steward of the world’s news. But the fact that Facebook itself is the one absolving Facebook of damaging public discourse, demands greater scrutiny. And on closer examination, much of the data and assumptions that informed the researchers’ conclusions fail to qualify as sound scientific inquiry.
First, let’s look at the hard data Facebook unearthed — which, admittedly, is in pretty short supply. Researchers found that after bringing its News Feed algorithm to bear on news stories posted by friends and pages, conservatives are 5 percent less likely to see stories they disagree with, while liberals are 8 percent less likely. That’s not a huge differential, and is maybe smaller than we might expect. Nevertheless, the data undoubtedly shows that Facebook’s algorithms do limit users’ exposure to stories they are likely to disagree with, or as Facebook calls them in the paper, “cross-cutting” stories.
But the researchers all but dismiss this inescapable fact by arguing that the real culprit behind a lack of cross-cutting in Facebook feeds are the users themselves, either because they don’t have enough friends with dissimilar views or because they don’t like clicking on stories that run counter to their beliefs. The friends of users who list their political affiliation as “liberal,” for example, only share conservative-leaning stories 24 percent of the time. The friends of users who list their political affiliation as “conservative,” meanwhile, only share liberal-leaning stories 35 percent of the time. Making matters worse, liberals only click on cross-cutting stories 7 percent of the time, while conservatives do so 17 percent of the time. So even without the influence of Facebook’s algorithmic twitches, liberals and conservatives both experience the effects of an echo chamber on social media.
Even if we take the study at face value, just because user choices weigh heavily in limiting one’s exposure to diverse political views, that doesn’t exonerate Facebook. It’s algorithms do the same, just not as strongly. But even this conclusion is suspect because the data set used by researchers is enormously limited. Communications professor Christian Sandvig, writing at Microsoft Research’s Social Media Collective blog, notes that researchers only evaluated feeds belonging to users who share a discernible political affiliation on their Facebook profile — which the professor estimates only makes up 4 percent of users. And because that’s such a specific behavioral trait, the test group is hardly what one would call “representative” of Facebook’s larger user base. With that in mind, this data — whether it’s interpreted in Facebook’s favor or against it — doesn’t tell us much of anything at all.
The researchers also betray their motives by adopting a tone that is self-serving and even defensive, suggesting that in spite of whatever limiting effects Facebook’s algorithm brings to bear on cross-cutting content, it shouldn’t matter because social media users are ultimately “exposed to more cross-cutting discourse in social media they would be under the digital reality envisioned by some,” before linking to a 2001 book about how hyper-personalization may threaten democracy.
“Perhaps this could be a new Facebook motto used in advertising,” Sandvig writes. “‘Facebook: Better than one speculative dystopian future!’”
So a corporation smuggled some PR into a scientific paper and some journalists fell for it. Somewhere, an angel got his wings and a publicist got a promotion.
But there’s nothing trivial about Facebook’s ambitions to become the predominant source for news content and a gatekeeper of information that rivals Google in its power over what we know. And even if Facebook’s algorithms play over a negligible role in contributing to echo chambers and polarization, there’s an argument to be made that Facebook, which has never been shy in the past about policing what content users see, has a responsibility as a major news distributor to use its algorithm to counteract the effects of users’ self-made bubbles, placing more weight on cross-cutting stories in News Feeds belonging to users with stated political affiliations. Supporters of completely free and open content networks may bristle at that suggestion, but Facebook already exerts a great deal of control over what users see, as it constantly tweaks and tinkers with its News Feed algorithm. And if it must continue to mold and alter the shape of our News Feeds, then perhaps it could do so in ways that better its users as news consumers, deemphasizing or even exorcizing false or plagiarized stories while promoting a measure of ideological balance.
But anyone with a knowledge of Facebook’s brief history in public relations knows exactly how the company would respond to this suggestion. It would raise the same defense it always does when critics foolishly attempt to hold Facebook to standards of journalistic ethics: By claiming it’s “user-first.”
As recently as last month, Facebook played the “user-first” card in response to criticism over changes it made to its News Feed algorithm that deemphasized content shared by pages belonging to brands — including news organizations. It doesn’t take a wizard of business to know why Facebook would make this change. As engagement and referrals surrounding this content inevitably falls, news organizations that have become reliant on Facebook for traffic will need that fix and do whatever’s necessary to get it. Chiefly, that means running paid promotions on Facebook to ensure users see these posts — promotions that make Facebook even richer.
But there’s a darker side to this: Changes like this create a “pay-to-play” paradigm wherein only the most well-funded news organizations are afforded the enormous reach Facebook can offer. This state of affairs tends to crowd out smaller outlets — many of whom are smaller because they value journalistic bravery over brand-friendliness — which is as harmful to public discourse as the political polarization Facebook examined in yesterday’s study. And just like it did in its study on polarization, Facebook blamed users for the controversial News Feed change, declaring that its data team had crunched the numbers and found that users liked it better when they saw fewer posts from news sites. Of course, by crunching the numbers, Facebook merely meant that it ran a survey, and the questions it asked of users were magnificently leading. Questions like, “Are you worried about missing important updates from the friends you care about?” seemed to be carefully designed to goad users into saying they preferred an outcome that just so happened to be perfectly aligned with Facebook’s business interests.
So of course, everyone’s going to answer yes to that. But does that mean users don’t care about other types of posts? It doesn’t matter. This is what Facebook does, and this is what it just did with its latest scientific paper. Whenever it receives criticism or wishes to carry out something potentially controversial, it saves face by taking messy or incomplete or subjective data and twisting it so that users shoulder the blame.
And therein lies the insidious brilliance of the News Feed algorithm. Contrary to what its polarization study suggests, Facebook’s algorithms and the behavior of its users are not two separate and discrete forces. The work done by the algorithm is heavily informed by user behavior, but not entirely. And to what degree and under what circumstances user behavior holds sway is not always clear. This makes any comparison between the two highly muddled and confused — which is just how Facebook likes it. That way, the company can attribute virtually any negative consequence of any algorithm-driven efforts to maximize profit or influence to the behavioral whims of its users. The News Feed algorithm is at once a black box and a magic wand.
Facebook wants to be taken seriously by journalistic organizations as part of its play to host news content directly. But whenever critics raise concerns about changes made to its algorithms which, incidentally or purposefully, limit users’ exposure to certain types of news content, Facebook casts off its responsibility to any higher ideals of journalistic integrity. Thanks to the knot of human and algorithmic influences that impact the News Feed, which by design are impossible for outsiders to untangle, it’s able to argue — with science! — that it’s beholden only to users and the “user experience.” If politically polarized users want politically polarized content, Facebook won’t disappoint them.
But this user-first defense is disingenuousness, particularly in light of Facebook’s broader monetization strategies and its ambitions to control how the news media reaches audiences. It’s old hat to say that if you’re not paying for a product, the product is you. But when it comes to Facebook, few cliches hold more true. The company’s core constituencies are advertisers and other brands that pay for exposure on its platform, and many of Facebook’s product changes –like its most recent News Feed tweak which encourages organizations to pay or partner with the company to reach users — are aligned with its endeavors to boost its revenue and influence and not, as Facebook innocently claims, to create a “better user experience.”
In what’s becoming an enormously troubling trend among corporations, Facebook will only continue to use slippery data as a weapon in its war with the public and its competitors over the company’s public image. The Internet has made it possible to fact-check anything, and laypeople have become more adept than ever at identifying spin and other deceitful rhetorical techniques native to public relations. That’s why it’s so brilliant and insidious to see Facebook farm out what’s traditionally the work of PR specialists to data scientists. On top of the intellectual cachet society affords them as Silicon Valley geek-idols, these whiz kids breathe the rarefied air of academics, appearing in Science which, despite a reputation that’s waned a bit — probably owing to its willingness to give lousy corporate data research like a pass — is still exponentially more credible than a rewritten press release at Techcrunch. Most readers won’t think twice, nor will many tech journalists who will blindly rephrase studies like these without really examining the quality of the data or the subjective assumptions put forth by the authors.
But don’t be fooled by the fancy diagrams and annotations. This isn’t science. It’s pro-Facebook propaganda.
David Holmes is Pando’s East Coast Editor. He is also the co-founder of Explainer Music, a production company specializing in journalistic music videos. His work has appeared at FastCompany.com, ProPublica, the Guardian, the Daily Dot, NewYorker.com, and Grist.