The PR BlogDigital PRData-Driven PRThe Silent Switch—A Stealthy Death for the Social Graph

The Silent Switch — A Stealthy Death for the Social Graph

How algorithms are replacing substance with sensationalism.

Cover photo: @jerrysilfwer

How is the silent switch impact­ing your content?

As a PR adviser since 2005 and a digit­al strategist since 2007, I’ve seen the silent switch take over — one seam­less iter­a­tion after another.

In this blog art­icle, I explain how social media algorithms silently have been cent­ral­ised into a series of glob­al Pavlovian experiments.

As PR- and com­mu­nic­a­tions pro­fes­sion­als, we should all be aware of what has happened — and what’s still happening.

Let’s dive right in:

Having Subscribers is Becoming Less and Less Important

Like many oth­ers inter­ested in pho­to­graphy, I sub­scribe to the Canadian con­tent cre­at­or Peter McKinnon on YouTube. I’m not alone — 5,55 mil­lion sub­scribers fol­low McKinnon as I write this.

5,55 mil­lion is a respect­able audi­ence; mil­lions of YouTube users have act­ively chosen to fol­low McKinnon’s future updates.

Peter McKinnon
Why won’t YouTube show all of Peter McKinnon’s videos to “his” subscribers?

Still, it’s not uncom­mon for McKinnon’s reg­u­lar videos to acquire only a few hun­dred thou­sand views.

Don’t get me wrong: I’m not say­ing that a few hun­dred thou­sand views are some­thing to sneeze at. And I’m not say­ing we should feel sorry for online mega-influ­en­cers, either.

I’m ask­ing why acquir­ing social media sub­scribers, fans, and fol­low­ers seems less sig­ni­fic­ant today. After all, fol­low­ers drive most con­tent cre­at­ors to social media in the first place.

A few hun­dred thou­sand views is a lot — but it’s not 5,55 mil­lion. And it’s reas­on­able to assume that 5,55 mil­lion sub­scribers haven’t act­ively decided against watch­ing McKinnon’s video. The video just hasn’t been sug­ges­ted to them.

As fol­lows:

Earning many sub­scribers, fans, and fol­low­ers used to mat­ter a lot, but nowadays, it mat­ters less.

Another way of put­ting it: Although McKinnon has 5,55 mil­lion YouTube sub­scribers, it doesn’t mean his videos have that kind of reach. Something else is at play here.

The Silent Switch: The Death of Building Trust Over Time

So, why have Facebook, Instagram, LinkedIn, and many oth­er social net­works, gone through so much trouble to render sub­scribers, fans, and fol­low­ers less valu­able to con­tent creators?

Here’s a his­tor­ic­al explanation:

In the early days of social net­works, feeds relied on net­work-based dis­tri­bu­tion — the more cent­ral the net­work node, the great­er the reach.

Clean and classy. If you wanted a high­er reach, you had to earn an audi­ence by estab­lish­ing trust over a more exten­ded period.

Today, oth­er types of selec­tion cri­ter­ia are dom­in­at­ing our social media feeds. Reach is rewar­ded not to con­tent cre­at­or author­ity but to indi­vidu­al con­tent pieces based on their single performance.

Wait, What? Network- vs Algorithmic Distribution

We have slowly moved from net­work dis­tri­bu­tion based on con­tent cre­at­or author­ity to algorithmic dis­tri­bu­tion based on single con­tent performance.

Instead of show­ing users con­tent based on who they’ve decided to fol­low, algorithms expose audi­ences to single con­tent pieces based on stand­ard­ised con­tent tests.

Network Effects - The Silent Switch
The mod­el shows two dif­fer­ent paradigms of dis­tri­bu­tion and influence.

The YouTube algorithm won’t show Peter McKinnon’s con­tent to all his 5,55 mil­lion subscribers.

Instead, YouTube shows a new McKinnon video to a small stat­ist­ic­al sub­set of users. If the video passes the small first test, the video is then shown to a slightly lar­ger stat­ist­ic­al subset.

And so on. 

The video could stop at 200,000 views — or climb to 2 bil­lion views. It depends on that single piece of con­tent, not how many fol­low­ers the cre­at­or has amassed. McKinnon’s 5,55 mil­lion sub­scribers are not as sig­ni­fic­ant in this new context.

Social Media Algorithms - Silent Shift - Doctor Spin - The PR Blog
How algorithms iter­ate to max­im­ise engage­ment and con­tent quality.

Okay, so what?

Doesn’t a suc­cess­ful vlog­ger like McKinnon already enjoy a massive reach at his fin­ger­tips? Aren’t power­ful online influ­en­cers already mak­ing enough money?

Here, we’re enter­ing into con­tro­ver­sial territory:

Why Tech Giants Are Switching Away

There are three main reas­ons social media tech giants move from net­work dis­tri­bu­tion to algorithmic distribution:

1. There’s a clash of desired out­comes. Network dis­tri­bu­tion doesn’t max­im­ise the type of engage­ment (i.e. ad clicks and expos­ure) social media tech giants seek to promote.

Online audi­ences seek to dis­trib­ute their trust spar­ingly and fol­low cre­at­ors who will psy­cho­lo­gic­ally emphas­ise how they see them­selves — they don’t fol­low con­tent cre­at­ors to increase their spend­ing or ad exposure.

2. Advanced serv­er-side com­pu­ta­tion is expens­ive. The com­plex­ity of social media algorithms is typ­ic­ally over­stated; the media is con­stantly buzz­ing about machine learn­ing, neur­al net­works, and arti­fi­cial intel­li­gence.

The prob­lem, how­ever, is that provid­ing advanced serv­er-side cal­cu­la­tions on user beha­viour in real-time is … expensive.

And apart from being expens­ive, this type of advanced ana­lyt­ics is likely to be GDPR-invas­ive and almost impossible to get right due to the com­plex­ity of human psychology.

3. Control is power; power is money. The algorithmic dis­tri­bu­tion gives the social net­work more con­trol over engage­ment. As a con­sequence, this removes con­trol from both audi­ences and con­tent creators.

This Is the Money Web

I love the idea of the social web. I love the idea of a demo­crat­ic and neut­ral space where every­one has a voice, com­munit­ies can form unbound by geo­graph­ic­al con­straints, and every­one is connected.

Here comes every­body,” Clay Shirky wrote.

Two dec­ades ago, the net­work-based Hippie Web (2005 – 2015) had a bur­geon­ing blo­go­sphere and lively for­ums where any­one dis­cussed ideas and joined togeth­er in com­munit­ies around causes and interests.

Social media optim­ists cited The Cluetrain Manifesto and fought for net neut­ral­ity. Sharing was caring.

One World One Web
Credit to Paul Downey for this beau­ti­ful illustration.

The wide­spread notion was that inform­a­tion wanted to be free, an ideo­logy spear­headed by open-source enthu­si­asts. We saw the advent of Napster and The Pirate Bay.

The Hippie Web was fun, but it had to end at some point.
We weren’t mak­ing enough money, frankly.

Enter the Money Web (2016 – present).

Today, suc­cess­ful influ­en­cers can earn a full-time liv­ing as online con­tent cre­at­ors. Not only that — they can get rich. We have a new and grow­ing cre­at­ive class of enter­tain­ers and educators.

The digit­al eco­nomy is grow­ing, and we reward those who can attract people’s atten­tion. Monetisation allows con­tent cre­at­ors to go full-time, which is impossible oth­er­wise. Having algorithms designed to get people to click on ads is essential.

But the algorithm own­ers are set­ting the stage, not the cre­at­ives. Content must drive clicks, and cre­at­ors must pro­duce con­tent that drives those clicks.

So what’s the Original Sin of the Internet? Nearly all busi­ness mod­els it sup­ports require spy­ing on con­sumers and mon­et­ising them.”
— Bob Sullivan, author and journalist 

Read also: Enter The Money Web (2016 – Present)

Sensationalism and Winner-Takes-All

The Silent Switch from net­work-based to algorithm-based dis­tri­bu­tion changes the game for every­one. Especially for us PR pro­fes­sion­als.

The Silent Switch

Not that long ago, social media algorithms would deliv­er organ­ic reach accord­ing to a dis­tri­bu­tion that looked like this:

The Silent Switch - Doctor Spin - The PR Blog.001
Social media algorithms before the silent switch (click to enlarge).

Today, social media algorithms deliv­er organ­ic reach more like this:

The Silent Switch - Doctor Spin - The PR Blog.002
Social media algorithms after the silent switch (click to enlarge).

It’s the Silent Switch where social net­works have demoted the pub­lish­er­’s author­ity and repu­ta­tion and pro­moted single con­tent per­form­ance instead.

This algorithmic change has likely had pro­found and severe media logic amplifications:

Classic Media Logic Effects

Media logic is hypo­thes­ised to influ­ence the news media in the fol­low­ing ways: 1Nord, L., & Strömbäck, J. (2002, January). Tio dagar som skakade världen. En stud­ie av medi­ernas beskrivningar av ter­ror­at­tack­erna mot USA och kri­get i Afghanistan hösten 2001. ResearchGate; … Continue read­ing

  • Aggravation. As a res­ult of media logic, the news media will exag­ger­ate events, con­cepts, and ideas to make them seem more ser­i­ous and/​or dan­ger­ous than they are.
  • Simplification. As a res­ult of media logic, the news media will dumb down events, con­cepts, and ideas to make them seem more under­stand­able than they are.
  • Polarisation. As a res­ult of media logic, the news media will por­tray events, con­cepts, and ideas as more conflicting/​provoking than they are.
  • Intensification. As a res­ult of media logic, the news media will sen­sa­tion­al­ise events, con­cepts, and ideas to make them more inter­est­ing than they are.
  • Concreteness. As a res­ult of media logic, the news media will report events, con­cepts, and ideas as more straight­for­ward than they are.
  • Personalisation. As a res­ult of media logic, the news media will over-emphas­ise the role of named indi­vidu­als in con­junc­tion with events, con­cepts, and ideas.
  • Stereotypisation. As a res­ult of media logic, the news media will frame events, con­cepts, and ideas as more aligned with con­ven­tion­al perceptions/​opinions than they are.

Social Media Logic Effects

  • Programmability. Social media logic enables and encour­ages users to cre­ate and manip­u­late con­tent, lead­ing to a tailored por­tray­al of events, con­cepts, and ideas that might not fully rep­res­ent reality.
  • Popularity. Driven by social media logic, con­tent that gains ini­tial pop­ular­ity can dis­pro­por­tion­ately influ­ence pub­lic per­cep­tion, regard­less of accur­acy or completeness.
  • Connectivity. Social medi­a’s inter­con­nec­ted nature, rein­forced by social media logic, facil­it­ates the rap­id spread of inform­a­tion, often without suf­fi­cient veri­fic­a­tion, lead­ing to a dis­tor­ted under­stand­ing of events and ideas.
  • Datafication. The social media logic of con­vert­ing inter­ac­tions into data points emphas­ises quan­ti­fi­able aspects of events, con­cepts, and ideas, poten­tially over­look­ing their qual­it­at­ive nuances.

Our job as PR pro­fes­sion­als is to help organ­isa­tions nav­ig­ate the media land­scape and com­mu­nic­ate more effi­ciently — espe­cially in times of change.

Read also: The Silent Switch: How Algorithms Have Changed

💡 Subscribe and get a free ebook on how to get bet­ter PR ideas.

For those of us who cre­ate online con­tent on behalf of an organ­isa­tion, the effects of the silent switch can be devastating.

On the “clas­sic” pre-money social web, where earn­ing sub­scribers, fans, and fol­low­ers, even not-so-spec­tac­u­lar cor­por­ate con­tent found its way to reas­on­able audi­ence sizes.

But on today’s Money Web, where algorithmic dis­tri­bu­tion dis­reg­ards earn­ing trust over earn­ing clicks, sen­sa­tion­al­ism pre­vails in a win­ner-takes-all scenario.

In a way, the play­ing field today is lev­elled. As long as you’re pre­pared to invest heav­ily in the risky busi­ness of cre­at­ing the type of sen­sa­tion­al con­tent that ulti­mately drives ads, that is.

Theoretically, algorithmic dis­tri­bu­tion should pro­duce bet­ter con­tent through competition.

But what con­sti­tutes “bet­ter?”

The prob­lem under this new paradigm is fun­da­ment­al — loy­alty and trust are non-rewar­ded behaviours.

A Global Pavlovian Experiment on Humans

I hear many people dis­cuss­ing online influ­en­cers. There’s a fas­cin­at­ing — and often pro­vok­ing! — allure to them.

The pro­voca­tion is apparent:

Many suc­cess­ful con­tent cre­at­ors pro­duce not­able earn­ings by churn­ing out sen­sa­tion­al content.

In a sense, the phe­nomen­on is not nov­el: Neil Postman warned us that we might amuse ourselves to death. And that was back in 1985!

Also, you don’t need to be an Ayn Rand ideo­lo­gist to sug­gest that private com­pan­ies strive for profits. No one forces Peter McKinnon and oth­er video cre­at­ors to play by YouTube’s rules.

But as PR pro­fes­sion­als, we must adapt and play by these new rules. We have no oth­er choice. Digital is way too prom­in­ent to be ignored:

Top Social Networks
Top social net­works via Statista​.com.

Tech giants have asked their audi­ences to per­mit them to run large-scale Pavlovian exper­i­ments on us. And they have giv­en it to them.

Pavlov Dogs - Doctor Spin - The PR Dog
We’re all just anim­als, right?

It’s no coin­cid­ence that terms of ser­vices are lengthy and hard-to-read dis­claim­er doc­u­ments designed for scrolling past while their main con­tent is dopam­ine-indu­cing click baits.

Love it, hate it. If you’re a PR pro­fes­sion­al, it doesn’t mat­ter.
If the play­book is chan­ging, so must we.

Those Who Crush the Algorithm

Content that attracts instant­an­eous momentum and makes a big splash through­out each iter­at­ive test­ing series will out­per­form oth­er con­tent types. 

As for YouTube, this is per­haps most clearly demon­strated by the record-break­ing MrBeast:

The fact that MrBeast has mil­lions of fol­low­ers on YouTube is not fun­da­ment­al for his con­tinu­ous suc­cess — his extra­vag­ant, over-the-top videos would go vir­al regard­less of which account pos­ted them. 2I’ve stud­ied sev­er­al in-depth inter­views with MrBeast, and it’s clear that he’s a bril­liant con­tent cre­at­or that has been pub­lish­ing videos on YouTube for a long time before his pub­lic … Continue read­ing

MrBeast - Largest Pizza - Thumbnail
“Are you not entertained?”

Here’s the point: Algorithmic dis­tri­bu­tion doesn’t mean con­tent cre­at­ors can’t reach a vast audi­ence. Innovative cre­at­ors, like MrBeast, will find ways to nego­ti­ate the algorithms and go vir­al repeatedly.

While we can appre­ci­ate MrBeast’s videos as wel­come dis­trac­tions, as pure dopam­ine-infused enter­tain­ment for the masses, we might be miss­ing out on con­tent cre­ated by indi­vidu­als and organ­isa­tions that could’ve reached their already-earned sub­scribers, fans, and followers.

Today, social media need user-gen­er­ated con­tent more than ever. But they don’t need mediocre cor­por­ate con­tent. They’d much rather have our budgets. 

For PR, this is rough but not unfair.

Why PR Professionals Must Adapt

Many organ­isa­tions have spent ser­i­ous resources attract­ing sub­scribers, fans, and fol­low­ers on social media. But the value of hav­ing sub­scribers, fans, and fol­low­ers is quickly eroding.

As PR pro­fes­sion­als, we must be rational.

We should com­pare the cur­rent situ­ation with our long-stand­ing rela­tion­ship with tra­di­tion­al news media. Traditional news media is power­ful but imper­fect, so PR pro­fes­sion­als must man­age the media. The same goes for social media.

It’s not our place as pro­fes­sion­al com­mu­nic­at­ors to tell journ­al­ists how to do their jobs, just as it isn’t our place to tell tech giants or con­tent cre­at­ors how to do their business.

Our job as PR pro­fes­sion­als is to help organ­isa­tions nav­ig­ate the com­plex­ity of the mod­ern media land­scape. Algorithms are a nat­ur­al part of that complexity.

The Silent Switch has pro­found and severe implic­a­tions for our soci­ety. But our job as PR pro­fes­sion­als isn’t to fix any of these prob­lems but to help organ­isa­tions com­mu­nic­ate effi­ciently in times of change.

Our job is identi­fy­ing sig­ni­fic­ant changes where the Silent Switch is fun­da­ment­al and find­ing ways to improve organ­isa­tion­al communication.

Please sup­port my PR blog by shar­ing it with oth­er com­mu­nic­a­tion pro­fes­sion­als. For ques­tions or PR sup­port, con­tact me via jerry@​spinfactory.​com.

PR Resource: The 7 Graphs of Algorithms

Types of Algorithm Graphs

Search engines, social net­works, and online ser­vices with large user bases all have a wealth of data to design and optim­ise the user experience. 

This data, when viewed through the lens of the sev­en types of graphs, forms the skel­et­on key to our digit­al identities:

  • Social Graph. The media com­pany can access your friend list and push their con­tent (or favoured con­tent) into your feed.
  • Interest Graph. The media com­pany can access your interests (top­ics, per­sons of interest, dif­fi­culty level, format pref­er­ences, on-plat­form-spe­cif­ic beha­viours etc.) from your usage history.
  • Predictive Graph. The media com­pany can access all graphs from users not con­nec­ted to you but with whom you share a stat­ist­ic­al like­ness and show their pre­ferred con­tent to you.
  • Prescriptive Graph. The media com­pany can push con­tent into your feed to manip­u­late your over­all emo­tion­al exper­i­ence of using the platform.
  • Trend Graph. The media com­pany can push con­tent into your feed based on what seems to be trend­ing on the platform.
  • Contextual Graph. The media com­pany can access con­tex­tu­al data like loc­a­tion, weath­er, cal­en­dar events, affil­i­ations, world events, and loc­al events.
  • Commercial Graph. The media com­pany can access data on how you and oth­ers like you inter­act with com­mer­cial content.

The dif­fer­ent graphs are typ­ic­ally weighted dif­fer­ently. For instance, some media com­pan­ies will allow a fair degree of social graph con­tent, while oth­ers almost none. Changes are con­stantly being enforced, and the Silent Switch might be the most not­able example where media com­pan­ies are shift­ing away from the social graph.

The media com­pany can lever­age these graphs using two main approaches:

  • Matching. The media com­pany can use vari­ous graphs to gen­er­ate your social feed. Depending on the com­plex­ity of the ana­lys­is, this approach is slow and expens­ive with react­ive (unpre­dict­able) results.
  • Profiling. The media com­pany can use vari­ous graphs to place you in stat­ist­ic­al sub­groups, allow­ing con­tent to iter­ate to the right audi­ence. This approach is fast and cheap with pro­act­ive (pre­dict­able) results.

Today, pro­fil­ing seems to be the dom­in­ant approach amongst media companies.

Learn more: The 7 Graphs of Algorithms: You’re Not Unknown

💡 Subscribe and get a free ebook on how to get bet­ter PR ideas.

1 Nord, L., & Strömbäck, J. (2002, January). Tio dagar som skakade världen. En stud­ie av medi­ernas beskrivningar av ter­ror­at­tack­erna mot USA och kri­get i Afghanistan hösten 2001. ResearchGate; Styrelsen för psyko­lo­giskt förs­var. https://​www​.researchg​ate​.net/​p​u​b​l​i​c​a​t​i​o​n​/​2​7​1​0​1​4​6​2​4​_​T​i​o​_​d​a​g​a​r​_​s​o​m​_​s​k​a​k​a​d​e​_​v​a​r​l​d​e​n​_​E​n​_​s​t​u​d​i​e​_​a​v​_​m​e​d​i​e​r​n​a​s​_​b​e​s​k​r​i​v​n​i​n​g​a​r​_​a​v​_​t​e​r​r​o​r​a​t​t​a​c​k​e​r​n​a​_​m​o​t​_​U​S​A​_​o​c​h​_​k​r​i​g​e​t​_​i​_​A​f​g​h​a​n​i​s​t​a​n​_​h​o​s​t​e​n​_​2​001
2 I’ve stud­ied sev­er­al in-depth inter­views with MrBeast, and it’s clear that he’s a bril­liant con­tent cre­at­or that has been pub­lish­ing videos on YouTube for a long time before his pub­lic breakthrough.
Jerry Silfwer
Jerry Silfwer
Jerry Silfwer, alias Doctor Spin, is an awarded senior adviser specialising in public relations and digital strategy. Currently CEO at Spin Factory and KIX Communication Index. Before that, he worked at Kaufmann, Whispr Group, Springtime PR, and Spotlight PR. Based in Stockholm, Sweden.

The Cover Photo

The cover photo isn't related to public relations; it's just a photo of mine. Think of it as a 'decorative diversion', a subtle reminder that there is more to life than strategic communication.

The cover photo has


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