Hate Cancel Culture? Blame the Algorithms

Image: Dolce & Gabbana

Hate Cancel Culture? Blame the Algorithms

“Cancel culture” has become so pervasive that even former President Barack Obama has weighed in on the phenomenon, describing it as an overly judgmental approach to activism that does little to bring about change. A novel but far-reaching aspect of modern culture, ...

February 12, 2020 - By TFL

Hate Cancel Culture? Blame the Algorithms

Image : Dolce & Gabbana

Case Documentation

Hate Cancel Culture? Blame the Algorithms

“Cancel culture” has become so pervasive that even former President Barack Obama has weighed in on the phenomenon, describing it as an overly judgmental approach to activism that does little to bring about change. A novel but far-reaching aspect of modern culture, cancel culture comes into play when an individual or an organization says, supports or promotes something that others find to be particularly offensive. As a result, the offended folks swarm, piling on the criticism via social media channels, making it so that the person or company is largely shunned … or “canceled.” 

It happened to Chick-fil-A when its ties to organizations, such as Focus on the Family, invited backlash from LGBTQ activists; it happened to YouTube influencer James Charles, who was accused of betraying his former mentor and then lost millions of followers as a result; and it happened to Miami Dolphins owner and the developer behind New York mega-mall Hudson Yards, Stephen Ross, after people learned he had held a fundraiser for President Trump. Not to be overlooked: Dolce & Gabbana, the men and the brand, who came under fire over what was largely deemed to be a racist ad campaign featuring a Chinese model eating pizza with chopsticks, followed by the dissemination of racist comments from co-founder Stefano Gabbana’s personal Instagram account.  

In most instances, the outrage can spread so quickly on social media that companies and/or individuals who do not adequately respond to a mishap – intentionally or otherwise – can face swift backlash. You can send a “stupid” tweet before boarding a flight and, upon landing, realize you have become the target of global ire.

A lot of attention has been given to repercussions of cancel culture on celebrities and famous brands, whether that takes the form of them losing gigs, having their products shunned by consumers, or losing followers on social media. Far less talked-about is the way that algorithms actually perpetuate cancel culture, especially since research has shown that content that sparks an intense emotional responses – positive or negative – is more likely to go viral.

Out of the millions of tweets, posts, videos and articles that are published each day, social media users can be exposed to only a limited amount. So, platforms write algorithms that curate news feeds to maximize engagement; social media companies, after all, want you to spend as much time on their platforms as possible. Outrage is the perfect negative emotion to attract attention and engagement – and algorithms are primed to pounce.

One non-famous person tweeting her outrage would normally fall largely on deaf ears, but if that one person is able to attract enough initial engagement, algorithms will extend her reach by promoting it to like-minded individuals. A snowball effect occurs, creating a feedback loop that amplifies the outrage far beyond her own pool of followers.

It is not uncommon for this outrage to lack context or otherwise be misleading; off-the-cuff tweets are not the same as heavily-edited, context-rich articles, after all. Maybe unsurprisingly, that lack of a full picture can work in favor of the reach of such a tweet. In fact, misleading content on social media tends to lead to even more engagement than verified information. 

Cancel culture is just one outgrowth of social media algorithms. Just as people have criticized how algorithms such as YouTube’s actively promote divisive posts in order to suck people into spending more time online, and just as 2018 British Parliament committee report on fake news criticized Facebook’s “relentless targeting of hyper-partisan views, which play to the fears and prejudices of people,” social media algorithms have a hand in helping to perpetuate cancel culture.  

But the role of algorithms does not stop there.

Paradoxically, the same algorithmic forces that support cancel culture can actually have a hand in rehabilitating those same canceled brands and/or individuals. For instance, a few months after Kevin Hart was “cancelled” over a series of homophobic tweets from 2009 to 2011, Netflix decided to produce two shows featuring the comedian. Why would Netflix expose itself to criticism by elevating a supposedly canceled celebrity? Because it knew that there would be an audience for Hart’s comedy – and that, in certain circles, the fact that he had been canceled oddly made him that much more famous and relevant. 

There is also the likelihood that Netflix’s own algorithms – paired with the massive amount of granular data it has on its subscribers – suggested that no small number of users would be predisposed to watching a show about Hart, despite the fact that he had been “canceled.”

As for whether that is why more than a dozen celebrities – from Keanu Reeves and Dwayne Wade to Reese Witherspoon and Sofia Vergara – wore Dolce & Gabbana creations either on the red carpet at the Oscars this weekend or to the official Vanity Fair after party just over a year after their massive “cancel” scandal is another matter. That seems to speak to the potentially very fleeting nature of cancel culture and to question its actual ability to tangibly break brands at a time dominated by an inherently hectic social sphere rife with incessant headline-making news. It is also not uncommon for consumers, in the midst of so much distraction, to forget in due course why they were even angry to begin with, assuming that they were ever willing to translate their online anger into concrete purchasing decisions in the first place. 

Anjana Susarla is an Associate Professor of Information Systems at Michigan State University. Edits/additions courtesy of TFL.

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