Facebook Demetricator, Go Rando, and Textbook in Fast Company Co.Design

Kelsey Campbell-Dollaghan of Fast Company’s Co.Design, writing about alternatives to #DeleteFacebook, discussed my works Facebook Demetricator, Go Rando, and Textbook. My favorite quote:

[Grosser] built several Chrome extensions that throw Facebook’s carefully honed algorithms into chaos—like lobbing a digital smoke bomb on your News Feed.

Might have to put that in my bio :) Read the full article here.

My Facebook-related works in The Washington Post

In the wake of the latest news about Cambridge Analytica, I spoke with The Washington Post yesterday. In an article titled Facebook is experimenting on you. Here’s how you can run an experiment on it, Abby Ohlheiser wrote:

Moments of crisis like these prompt soul searching. If you’re one of those wondering, in the days since this scandal, why you give so much information to Facebook in the first place — or even if you should quit the site altogether — Grosser has a series of tools that can help you interrogate what it is that Facebook has done to you.

Abby writes a great blog on The Washington Post called The Intersect, examining how the culture of the internet has become an inseparable part of our lives; I recommend you keep an eye on it.

Read the full article: Facebook is experimenting on you. Here’s how you can run an experiment on it.

Twitter Demetricator in Slate

Slate Magazine’s chief technology writer, Will Oremus, wrote an insightful piece analyzing Twitter Demetricator and its effects. Speaking about his initial impressions of Twitter without the metrics:

Without really meaning to, I’d been glossing over tweets that had relatively few likes and paying extra attention to those that had many. I had even subconsciously developed a sort of multiplier for various Twitter users based on the size of their followings, so that a tweet by a relatively obscure user that garnered 10 likes would stand out in my feed more than one by a famous user that got 100 likes. And in threads with lots of replies, I had been checking like counts as though they were an official scorecard of who was “winning” the conversation.

Later, he reflects on his experience:

…you might be surprised at how drastically you can change your Facebook or Twitter experience just by hiding a few little numbers. Indeed, it’s almost impossible to comprehend just how central metrics are to the Twitter experience until you install Demetricator. Only when I tried it did I realize that my eyes were instinctively flicking to a tweet’s retweet and favorite counters before I even processed the tweet itself. Only when I tried Demetricator did I understand how much I relied on those signals to evaluate a tweet—not only its popularity or reach, but its value.

Will contextualizes his impressions within the current moment, when social media companies are under siege for their roles in everything from their effects on mental health to the ways they were weaponized in the recent US election.

I’ve been reading Will’s writing for years, as he’s one of the best journalists out there analyzing technology from a broader perspective. I encourage you to read the whole piece.

Twitter Demetricator in The New Yorker

My latest project, Twitter Demetricator, is a browser extension that removes all visible metrics from the Twitter interface. On the day of its release, the work was also the subject of a fantastic article in The New Yorker by author David Zweig. David spent a few weeks with the work as part of a private beta test, and then artfully reflected on his experience. I recommend you read the whole text, but here’s an excerpt:

After three weeks of using the Demetricator, the nature of Twitter, for me, changed completely. In some ways, it became lonelier. Part of the fun had been feeling like part of a crowd, seeing a joke or an idea or an observation become something that fifty people, or fifty thousand, could share. But I’m willing to accept the loss of this superficial sense of community for all the gains. Not seeing any numbers at all made content itself the king. I came to appreciate, disconcertingly, that knowing what was popular before had not only often distorted but also sometimes completely overtaken my experience. With the numbers gone, I realized that they, indeed, had forced a sort of automated experience, guiding and constraining my behavior.

The way that Twitter’s visible metrics were helping David feel “like part of a crowd” is one of my interests with this new Demetricator. While Twitter’s like, retweet, and follower metrics are similar—in principle—to Facebook’s like, share, and friend metrics, there’s definitely some important differences in how these metrics engineer user experience. On Facebook, likes/shares/etc are mostly constrained in size by one’s “friend” network, while on Twitter they are unconstrained. At any time, any Tweet’s metrics could reach not just into the hundreds of likes, but into the thousands or even millions. I’m guessing the sheer scale of this potential reaction activates our “desire for more” well beyond what users experience with Facebook. How does this expanded scale of potential reaction affect what David describes as a numbers-driven “automated experience” that guides and constrains behavior? That’s one of the questions I’ll be thinking about in the coming weeks.

Read about or install Twitter Demetricator, or go to the New Yorker and read David’s piece about it.