Posts about journalism

Trafficking in traffic

May 1, 2023 by Jeff Jarvis
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Ben Smith picked just the right title for his saga of BuzzFeed, Gawker, and The Huffington Post: Traffic (though in the end, he credits the able sensationalist Michael Wolff with the choice). For what Ben chronicles is both the apotheosis and the end of the age of mass media and its obsessive quest for audience attention, for scale, for circulation, ratings, page views, unique users, eyeballs and engagement. 

Most everything I write these days — my upcoming books The Gutenberg Parenthesis in June and a next book, an elegy to the magazine in November, and another that I’m working on about the internet — is in the end about the death of the mass, a passing I celebrate. I write in The Gutenberg Parenthesis: 

The mass is the child and creation of media, a descendant of Gutenberg, the ultimate extension of treating the public as object — as audience rather than participant. It was the mechanization and industrialization of print with the steam-powered press and Linotype — exploding the circulation of daily newspapers from an average of 4,000 in the late nineteenth century to hundreds of thousands and millions in the next — that brought scale to media. With broadcast, the mass became all-encompassing. Mass is the defining business model of pre-internet capitalism: making as many identical widgets to sell to as many identical people as possible. Content becomes a commodity to attract the attention of the audience, who themselves are sold as a commodity. In the mass, everything and everyone is commodified.

Ben and the anti-heroes of his tale — BuzzFeed founder Jonah Peretti, Gawker Media founder Nick Denton, HuffPost founder Arianna Huffington, investor Kenny Lerer, and a complete dramatis personae of the early players in pure-play digital media — were really no different from the Hearsts, Pulitzers, Newhouses, Luces, Greeleys, Bennetts, Sarnoffs, Paleys, and, yes, Murdochs, the moguls of mass media’s mechanized, industrialized, and corporate age who built their empires on traffic. The only difference, really, was that the digital moguls had new ways to hunt their prey: social, SEO, clickbait, data, listicles, and snark.

Ben tells the story so very well; he is an admirable writer and reporter. His narrative whizzes by like a local train on the express tracks. And it rings true. I had a seat myself on this ride. I was a friend of Nick Denton’s and a member of the board of his company before Gawker, Moreover; president of the online division of Advance (Condé Nast + Newhouse Newspapers); a board member for another pure-play, Plastic (a mashup of Suck et al); a proto-blogger; a writer for HuffPost; and a media critic who occasionally got invited to Nick’s parties and argued alongside Elizabeth Spiers at his kitchen table that he needed to open up to comments (maybe it’s all our fault). So I quite enjoyed Traffic. Because memories.

Traffic is worthwhile as a historical document of an as-it-turns-out-brief chapter in media history and as Ben’s own memoir of his rise from Politico blogger to BuzzFeed News editor to New York Times media critic to co-founder of Semafor. I find it interesting that Ben does not try to separate out the work of his newsroom from the click-factory next door. Passing reference is made to the prestige he and Jonah wanted news to bring to the brand, but Ben does not shy away from association with the viral side of the house. 

I saw a much greater separation between the two divisions of BuzzFeed — not just reputationally but also in business models. It took me years to understand the foundation of BuzzFeed’s business. My fellow media blatherers would often scold me: “You don’t understand, Jeff,” one said, “BuzzFeed is the first data-driven newsroom.” So what? Every newsroom and every news organization since the 1850s measured itself by its traffic, whether they called it circulation or reach or MAUs. 

No, what separated BuzzFeed’s business from the rest was that it did not sell space or time or even audience. It sold a skill: We know how to make our stuff viral, they said to advertisers. We can make your stuff viral. As a business, it (like Vice) was an ad agency with a giant proof-of-concept attached.

There were two problems. The first was that BuzzFeed depended for four-fifths of its distribution on other platforms: BuzzFeed’s own audience took its content to the larger audience where they were, mostly on Facebook, also YouTube and Twitter. That worked fine until it didn’t — until other, less talented copykittens ruined it for them. The same thing happened years earlier to About.com, where The New York Times Company brought me in to consult after its purchase. About.com had answers to questions people asked in Google search, so Google sent them to About.com, where Google sold the ads. It was a beautiful thing, until crappy content farms like Demand Media came and ruined it for them. In a first major ranking overhaul, Google had to downgrade everything that looked like a content farm, including About. Oh, well. (After learning the skills of SEO and waiting too long, The Times Company finally sold About.com; its remnants labor on in Barry Diller’s content farm, DotDash, where the last survivors of Time Inc. and Meredith toil, mostly post-print.)

The same phenomenon struck BuzzFeed, as social networks became overwhelmed with viral crap because, to use Silicon Valley argot, there was no barrier to entry to making clickbait. In Traffic, Ben reviews the history of Eli Pariser’s well-intentioned but ultimately corrupting startup Upworthy, which ruined the internet and all of media with its invention, the you-won’t-believe-what-happened-next headline. The experience of being bombarded with manipulative ploys for attention was bad for users and the social networks had to downgrade it. Also, as Ben reports, they discovered that many people were more apt to share screeds filled with hate and lies than cute kittens. Enter Breitbart. 

BuzzFeed’s second problem was that BuzzFeed News had no sustainable business model other than the unsustainable business model of the rest of news. News isn’t, despite the best efforts of headline writers, terribly clickable. In the early days, BuzzFeed didn’t sell banner ads on its own content and even if it had, advertisers don’t much want to be around news because it is not “brand safe.” Therein lies a terrible commentary on marketing and media, but I’ll leave that for another day. 

Ben’s book comes out just as BuzzFeed killed News. In the announcement, Jonah confessed to “overinvesting” in it, which is an admirably candid admission that news didn’t have a business model. Sooner or later, the company’s real bosses — owners of its equity — would demand its death. Ben writes: “I’ve come to regret encouraging Jonah to see our news division as a worthy enterprise that shouldn’t be evaluated solely as a business.” Ain’t that the problem with every newsroom? The truth is that BuzzFeed News was a philanthropic gift to the information ecosystem from Jonah and Ben.

Just as Jonah and company believed that Facebook et al had turned on them, they turned on Facebook and Google and Twitter, joining old, incumbent media in arguing that Silicon Valley somehow owed the news industry. For what? For sending them traffic all these years? Ben tells of meeting with the gray eminence of the true evil empire, News Corp., to discuss strategies to squeeze “protection money” (Ben’s words) from technology companies. That, too, is no business model. 

Thus the death of BuzzFeed news says much about the fate of journalism today. In Traffic, Ben tells the tale of the greatest single traffic driver in BuzzFeed’s history: The Dress. You know, this one: 

At every journalism conference where I took the stage after that, I would ask the journalists in attendance how many of their news organizations wrote a story about The Dress. Every single hand would go up. And what does that say about the state of journalism today? As we whine and wail about losing reporters and editors at the hands of greedy capitalists, we nonetheless waste tremendous journalistic resource rewriting each other for traffic: everyone had to have their own story to get their own Googlejuice and likes and links and ad impressions and pennies from them. No one added anything of value to BuzzFeed’s own story. The story, certainly BuzzFeed would acknowledge, had no particular social value; it did nothing to inform public discourse. It was fun. It got people talking. It took their attention. It generated traffic. 

The virus Ben writes about is one that BuzzFeed — and the every news organization on the internet and the internet as a whole — caught from old, coughing mass media: the insatiable hunger for traffic for its own sake. In the book, Nick Denton plays the role of inscrutable (oh, I can attest to that) philosopher. According to Ben, Nick believed that traffic was the key expression of value: “Traffic, to Nick … was something pure. It was an art, not a science. Traffic meant that what you were doing was working.” Yet Nick also knew where traffic could lead. Ben quotes him telling a journalist in 2014: “It’s not jonah himself I hate, but this stage of internet media for which he is so perfectly optimized. I see an image of his cynical smirk — made you click! — every time a stupid buzzfeed listicle pops on Facebook.”

Nick also believed that transparency was the only ethic that really mattered, for the sake of democracy. Add these two premises, traffic and transparency, together and the sex tape that was the McGuffin that brought down Gawker and Nick at the hands of Peter Thiel was perhaps an inevitability. Ben also credits (or blames?) Nick for his own decision to release the Trump dossier to the public on BuzzFeed. (I still think Ben has a credible argument for doing so: It was being talked about in government and in media and we, the public, had the right to judge for ourselves. Or rather, it’s not our right to decide; it’s a responsibility, which will fall on all of us more and more as our old institutions of trust and authority — editing and publishing — falter in the face of the abundance of talk the net enables.)

The problem in the end is that traffic is a commodity; commodities have no unique value; and commodities in abundance will always decrease in price, toward zero. “Even as the traffic to BuzzFeed, Gawker Media, and other adept digital publishers grew,” Ben writes, “their operators began to feel that they were running on an accelerating treadmill, needing ever more traffic to keep the same dollars flowing in.” Precisely

Traffic is not where the value of the internet lies. No, as I write in The Gutenberg Parenthesis (/plug), the real value of the internet is that it begins to reverse the impact print and mass media have had on public discourse. The internet devalues the notions of content, audience, and traffic in favor of speech. Only it is going to take a long time for society to relearn the conversational skills it has lost and — as with Gutenberg and the Reformation, Counter-Reformation, and Thirty Years’ War that followed — things will be messy in between. 

BuzzFeed, Gawker, The Huffington Post, etc. were not new media at all. They were the last gasp of old media, trying to keep the old ways alive with new tricks. What comes next — what is actually new — has yet to be invented. That is what I care about. That is why I teach. 

Journalism is lossy compression

February 12, 2023 by Jeff Jarvis
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There has been much praise in human chat — Twitter — about Ted Chiang’s New Yorker piece on machine chat — ChatGPT. Because New Yorker; because Ted Chiang. He makes a clever comparison between lossy compression — how JPEGs or MP3s save a good-enough artifact of a thing, with some pieces missing and fudged to save space — and large-language models, which learn from and spit back but do not record the entire web. “Think of ChatGTP as a blurry JPEG of all the text on the Web,” he instructs. 

What strikes me about the piece is how unselfaware media are when covering technology.

For what is journalism itself but lossy compression of the world? To save space, the journalist cannot and does not save or report everything known about an issue or event, compressing what is learned into so many available inches of type. For that matter, what is a library or a museum or a curriculum but lossy compression — that which fits? What is culture but lossy compression of creativity? As Umberto Eco said, “Now more than ever, we realize that culture is made up of what remains after everything else has been forgotten.”

Chiang analogizes ChatGPT et al to a computational Xerox machine that made an error because it extrapolated one set of bits for others. Matthew Kirschenbaum quibbles:

Agreed. This reminds me of the sometimes rancorous debate between Elizabeth Eisenstein, credited as the founder of the discipline of book history, and her chief critic, Adrian Johns. Eisenstein valued fixity as a key attribute of print, its authority and thus its culture. “Typographical fixity,” she said, “is a basic prerequisite for the rapid advancement of learning.” Johns dismissed her idea of print culture, arguing that early books were not fixed and authoritative but often sloppy and wrong (which Eisenstein also said). They were both right. Early books were filled with errors and, as Eisenstein pointed out, spread disinformation. “But new forms of scurrilous gossip, erotic fantasy, idle pleasure-seeking, and freethinking were also linked” to printing, she wrote. “Like piety, pornography assumed new forms.” It took time for print to earn its reputation of uniformity, accuracy, and quality and for new institutions — editing and publishing — to imbue the form with authority. 

That is precisely the process we are witnessing now with the new technologies of the day. The problem, often, is that we — especially journalists — make assumptions and set expectations about the new based on the analog and presumptions of the old. 

Media have been making quite the fuss about ChatGPT, declaring in many a headline that Google better watch out because it could replace its Search. As we all know by now, Microsoft is adding ChatGPT to its Bing and Google is said to have stumbled in its announcements about large-language models and search last week. 

But it’s evident that the large-language models we have seen so far are not yet good for search or for factual divination; see the Stochastic Parrots paper that got Tinmit Gebru fired from Google; see also her coauthor Emily Bender’s continuing and cautionary writing on the topic. Then read David Weinberger’s Everyday Chaos, an excellent and slightly ahead of its moment explanation of what artificial intelligence, machine learning, and large language models do. They predict. They take their learnings — whether from the web or some other large set of data — and predict what might happen next or what should come next in a sequence of, say, words. (I wrote about his book here.) 

Said Weinberger: “Our new engines of prediction are able to make more accurate predictions and to make predictions in domains that we used to think were impervious to them because this new technology can handle far more data, constrained by fewer human expectations about how that data fits together, with more complex rules, more complex interdependencies, and more sensitivity to starting points.”

To predict the next, best word in a sequence is a different task from finding the correct answer to a math problem or verifying a factual assertion or searching for the best match to a query. This is not to say that these functions cannot be added onto large-language models as rhetorical machines. As Google and Microsoft are about to learn, these functions damned well better be bolted together before LLMs are unleashed on the world with the promise of accuracy. 

When media report on these new technologies they too often ignore underlying lessons about what they say about us. They too often set high expectations — ChatGPT can replace search! — and then delight in shooting down those expectations — ChatGPT made mistakes!

Chiang wishes ChatGPT to search and calculate and compose and when it is not good at those tasks, he all but dismisses the utility of LLMs. As a writer, he just might be engaging in wishful thinking. Here I speculate about how ChatGPT might help expand literacy and also devalue the special status of the writer in society. In my upcoming book, The Gutenberg Parenthesis (preorder here /plug), I note that it was not until a century and a half after Gutenberg that major innovation occurred with print: the invention of the essay (Montaigne), the modern novel (Cervantes), and the newspaper. We are early our progression of learning what we can do with new technologies such as large-language models. It may be too early to use them in certain circumstances (e.g., search) but it is also too early to dismiss them.

It is equally important to recognize the faults in these technologies — and the faults that they expose in us — and understand the source of each. Large-language models such as ChatGPT and Google’s LaMDA are trained on, among other things, the web, which is to say society’s sooty exhaust, carrying all the errors, mistakes, conspiracies, biases, bigotries, presumptions, and stupidities — as well as genius — of humanity online. When we blame an algorithm for exhibiting bias we should start with the realization that it is reflecting our own biases. We must fix both: the data it learns from and the underlying corruption in society’s soul. 

Chiang’s story is lossy in that he quotes and cites none of the many scientists, researchers, and philosophers who are working in the field, making it as difficult as ChatGPT does to track down the source of his logic and conclusions.

The lossiest algorithm of all is the form of story. Said Weinberger:

Why have we so insisted on turning complex histories into simple stories? Marshall McLuhan was right: the medium is the message. We shrank our ideas to fit on pages sewn in a sequence that we then glued between cardboard stops. Books are good at telling stories and bad at guiding us through knowledge that bursts out in every conceivable direction, as all knowledge does when we let it.
But now the medium of our daily experiences — the internet — has the capacity, the connections, and the engine needed to express the richly chaotic nature of the world.

In the end, Chiang prefers the web to an algorithm’s rephrasing of it. Hurrah for the web. 

We are only beginning to learn what the net can and cannot do, what is good and bad from it, what we should or should not make of it, what it reflects in us. The institutions created to grant print fixity and authority — editing and publishing — are proving inadequate to cope with the scale of speech (aka content) online. The current, temporary proprietors of the net, the platforms, are also so far not up to the task. We will need to overhaul or invent new institutions to grapple with issues of credibility and quality, to discover and recommend and nurture talent and authority. As with print, that will take time, more time than journalists have to file their next story.

 Original painting by Johannes Vermeer; transformed (pixelated) by acagastya., CC0, via Wikimedia Commons

Writing as exclusion

December 22, 2022 by Jeff Jarvis
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DALL-E image of quill, ink pot, and paper with writing on it.
DALL-E

In The Gutenberg Parenthesis (my upcoming book), I ask whether, “in bringing his inner debates to print, Montaigne raised the stakes for joining the public conversation, requiring that one be a writer to be heard. That is, to share one’s thoughts, even about oneself, necessitated the talent of writing as qualification. How many people today say they are intimidated setting fingers to keys for any written form — letter, email, memo, blog, social-media post, school assignment, story, book, anything — because they claim not to be writers, while all the internet asks them to be is a speaker? What voices were left out of the conversation because they did not believe they were qualified to write? … The greatest means of control of speech might not have been censorship or copyright or publishing but instead the intimidation of writing.”

Thus I am struck by the opportunity presented by generative AI — lately and specifically ChatGPT— to provide people with an opportunity to better express themselves, to help them write, to act as Cyrano at their ear. Fellow educators everywhere are freaking out, wondering how they can ever teach writing and assign essays without wondering whether they are grading student or machine. I, on the other hand, look for opportunity — to open up the public conversation to more people in more ways, which I will explore here.

Let me first be clear that I do not advocate an end to writing or teaching it — especially as I work in a journalism school. It is said by some that a journalism degree is the new English degree, for we teach the value of research and the skill of clear expression. In our Engagement Journalism program, we teach that rather than always extracting and exploiting others’ stories, we should help people tell their own. Perhaps now we have more tools to aid in the effort.

I have for some time argued that we must expand the boundaries of literacy to include more people and to value more means of expression. Audio in the form of podcasts, video on YouTube or TikTok, visual expression in photography and memes, and the new alphabets of emoji enable people to speak and be understood as they wish, without writing. I have contended to faculty in communications schools (besides just my own) that we must value the languages (by that I mean especially dialects) and skills (including in social media) that our students bring.

Having said all that, let us examine the opportunities presented by generative AI. When some professors were freaking out on Mastodon about ChatGPT, one prof — sorry I can’t recall who — suggested creating different assignments with it: Provide students with the product of AI and ask them to critique it for accuracy, logic, expression — that is, make the students teachers of the machines.

This is also an opportunity to teach students the limitations and biases of AI and large language models, as laid out by Timnit Gebru, Emily Bender, Margaret Mitchell, and Angelina McMillan-Major in their Stochastic Parrots paper. Users must understand when they are listening to a machine that is trained merely to predict the next most sensible word, not to deliver and verify facts; the machine does not understand meaning. They also must realize when the data used to train a language model reflects the biases and exclusions of the web as source — when it reflects society’s existing inequities — or when it has been trained with curated content and rules to present a different worldview. The creators of these models need to be transparent about their makings and users must be made aware of their limitations.

It occurs to me that we will probably soon be teaching the skill of prompt writing: how to get what you want out of a machine. We started exercising this new muscle with DALL-E and other generative image AI — and we learned it’s not easy to guide the machine to draw exactly what we have in mind. At the same time, lots of folks are already using ChatGPT to write code. That is profound, for it means that we can tell the machine how to tell itself how to do what we want it to do. Coders should be more immediately worried about their career prospects than writers. Illustrators should also sweat more than scribblers.

In the end, writing a prompt for the machine — being able to exactly and clearly communicate one’s desires for the text, image, or code to be produced — is itself a new way to teach self-expression.

Generative AI also brings the reverse potential: helping to prompt the writer. This morning on Mastodon, I empathized with a writer who lamented that he was in the “I’m at the ‘(BETTER WORDS TK)’ stage” and I suggested that he try ChatGPT just to inspire a break in the logjam. It could act like a super-powered thesaurus. Even now, of course, Google often anticipates where I’m headed with a sentence and offers a suggested next word. That still feels like cheating — I usually try to prove Google wrong by avoiding what I now sense as a cliché — but is it so bad to have a friend who can finish your sentences for you?

For years, AI has been able to take simple, structured data — sports scores, financial results — and turn that into stories for wire services and news organizations. Text, after all, is just another form of data visualization. Long ago, I sat in a small newsroom for an advisory board meeting and when the topic of using such AI came up, I asked the eavesdropping, young sports writer a few desks over whether this worried him. Not at all, he said: He would have the machine write all the damned high-school game stories the paper wanted so he could concentrate on more interesting tales. ChatGPT is also proving to be good at churning out dull but necessary manuals and documentation. One might argue, then, that if the machine takes over the most drudgerous forms of writing, we humans would be left with brainpower to write more creative, thoughtful, interesting work. Maybe the machine could help improve writing overall.

A decade ago, I met a professor from INSEAD, Philip Parker, who insisted that contrary to popular belief, there is not too much content in the world; there is too little. After our conversation, I blogged: “Parker’s system has written tens of thousands of books and is even creating fully automated radio shows in many languages…. He used his software to create a directory of tropical plants that didn’t exist. And he has radio beaming out to farmers in poor third-world nations.”

By turning text into radio, Parker’s project, too, redefines literacy, making listening, rather than reading or writing, the necessary skill to become informed. As it happens, in that post from 2011, I starting musing about the theory Tom Pettitt had brought to the U.S. from the University of Southern Denmark: the Gutenberg Parenthesis. In my book, which that theory inspired, I explore the idea that we might be returning to an age of orality — and aurality — past the age of text. Could we be leaving the era of the writer?

And that is perhaps the real challenge presented by ChatGPT: Writers are no longer so special. Writing is no longer a privilege. Content is a commodity. Everyone will have more means to express themselves, bringing more voices to public discourse — further threatening those who once held a monopoly on it. What “content creators” — as erstwhile writers and illustrators are now known — must come to realize is that value will reside not only in creation but also in conversation, in the experiences people bring and the conversations they join.

Montaigne’s time, too, was marked by a new abundance of speech, of writing, of content. “Montaigne was acutely aware that printing, far from simplifying knowledge, had multiplied it, creating a flood of increasingly specialized information without furnishing uniform procedures for organizing it,” wrote Barry Lydgate. “Montaigne laments the chaotic proliferation of books in his time and singles out in his jeremiad a new race of ‘escrivains ineptes et inutiles’ ‘inept and useless writers’ on whose indiscriminate scribbling he diagnoses a society in decay…. ‘Scribbling seems to be a sort of symptom of an unruly age.’”

Today, the machine, too, scribbles.

https://link.medium.com/35wnOIMyYvb

On joining Mastodon

November 21, 2022 by Jeff Jarvis
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An academic friend asked for help joining Mastodon. I wrote a detailed email in response that I thought it might be useful to others. I’m also going to teach a master class in Mastodon at my school on Dec. 5 — much interest, I’m told — so here is my preparation on the practical stuff. (I will also talk that day about the implications of federation on journalism and of affordances on communities such as Black Twitter.) Keep in mind that I am a newbie, so please correct me where where I stray.

It will be a pleasure to welcome you to the new neighborhood. I’m quite liking it already. Once you arrive, you’ll find it familiar enough: You have a home timeline, a feed of just the people you follow, but with no algorithmic promotion, no ads. You can write posts (the verb to “toot” has, mercifully, become to “publish”) and boost others’ posts (AKA retweet) and reply to posts. You will receive notifications when people respond to you, boost your posts, and follow you.

You cannot quote-tweet posts as of now because of the founder’s belief that this affordance leads to performative over conversational behavior. That contention is being contested by people from Black Twitter, who use quote tweets for their call-and-response culture. Dr. Johnathan Flowers is forceful and instructive on the topic. Lately, Eugen Rochko, (@gargron), Mastodon’s founder, has softened and said he open to discussion. Developers are making suggestions for how to make QTs work (which is the beauty of this open-source project; change is emergent).

The two things that befuddle people getting started are how to pick an instance or server to join and then how to find folks. Mastodon is actually a few thousand servers — or instances, in the parlance — that each run versions of the same software and are all connected or federated in what is called the Fediverse, using an open-source protocol called ActivityPub. Every instance is independently run but can connect to any or all of the other instances, allowing you to connect with anyone on them. Not all of them are Mastodon; there are, for example, other servers for a photo-based social network called Pixelfed. No one owns this; no one can. That is the value of open source and federation. (Here is a post I wrote that examines and explains some of the implications and opportunities of federation.)

It doesn’t greatly matter what server you join as in this federated ecosystem, you can follow and converse with anyone on any server (except those that your host blocks; for example, the far-right, noxious Gab is blocked by most). Each server has its own rules. I am on mastodon.social, which is the biggest and is run by Eugen (@gargron).

If you prefer to be among academics, you might look to join hcommons.social for humanities scholars (though it is temporarily closed to new members until they catch up to the flood) or zirk.us for arts and humanities, where I see lots of smart folks, or perhaps religion.masto.host. Here’s a list of alternatives from the Humanities commons and here is very good reference that lists academic servers. You can go to any server address and add explore — e.g., zirk.us/about — to learn more about the server: who runs it, what its rules are. For journalists, we at Tow-Knight are supporting Adam Davidson as he launches journa.host. There’s another called newsie.social. Note that various news organizations — including Rest of World, Texas Observer, and San Francisco Standard — are starting their own servers for their own newsrooms.My fellow geeks might want to join Leo Laporte’s twit.social; to manage the onslaught he is now restricting it to members of his club.

Don’t stress about the choice; just pick one and go with it.

The only real implications of joining a particular server are (1) that you can view a “local” timeline populated with the posts of all the people from that server and you might find that useful , and (2) you want a responsible host who is going to block the bad guys and moderate wisely. If once on Mastodon you find the grass greener on someone else’s server, you can take your identity and your followers and go there — that portability and interoperability is a key benefit and differentiation of the federated vs. the corporate and centralized internet. Keep in mind that the content you create on your first server stays there.

OK, to get started. Go to one of the addresses above, say zirk.us. Click sign up and you’ll be shown the rules of the house, and then pick your name and such. You’re in.

I strongly recommend that you first take the time to fill in your profile with information about you, with your photo, for as soon as you start following people, they will want to know who you are and follow you back if relevant. I find it frustrating to have folks following me without letting me know who they are. It is also recommended that you write an introduction post and pin that to the top of your profile. (If you have a blog or site of your own, you can connect the two so that readers can know you are who you say ou are by using the rel=“me” markup, but that’s a graduate-level course I’ll leave that for another day.)

You will start using the web interface for Mastodon. It’s good, though I have a few key recommendations. Go to the settings (the little gear icon on top left) and under preferences/appearance I strongly suggest selecting advanced web interface. This will look like Tweetdeck. I happen to hate dark mode in all instances, but on Mastodon, it’s particularly hard to adjust to, so I urge you to try light mode.

Now to the next challenge: following people, for until you find folks to follow, you will hear only silence. One way to start is to search for folks you know are on Mastodon and see whom they follow.

Mastodon provides another fantastic way to get a starter kit: Under settings, import and export, click on import and here you can upload lists of folks to follow. For my friend to whom I wrote a version of this email, a book historian, I provided a list of book historians someone has compiled and a list of folks from my Book History Wonks Twitter list. Here is a wonderful list of lists of academics by discipline. Here is an incredibly long list of more than a thousand journalists on Mastodon (unless a masochist for hot takes, I would not suggest uploading them all).

Some of these provide a ready-made CSV to import. If not, copy just the column of Mastodon addresses into a new spreadsheet and save as a CSV. Upload the CSV file into Mastodon under settings/upload (you want to check the merge option). Voilà, you have new friends.

If you wish, you can use debirdify or fedifinder to check your own followers on Twitter for accounts that have Mastodon addresses. Click “search followed accounts” and it will produce a list and a CSV file. Since more and more folks are doing this, you will probably want to go back to your Twitter profile and add your new, forwarding address. My address, for example, is @jeffjarvis.

By the way, Mastodon does not have a good, full-text search — on purpose (for they also believe that that enables trolls to find their targets). But you can search for names, Mastodon addresses, and hashtags.

Now let’s explore the advanced web interface for Mastodon.

The second column from the left is the most important: your home timeline. This, again, is just the people you follow in reverse-chronological order; no algo, no ads.

The third column is notifications. Once you get your sea legs, click on the settings icon on the top right of the column (the three lines) and you’ll find a plethora of choices for what notifications to receive or not: new followers, posts that mention you, replies to you, and so on. While you’re here, I recommend turning OFF sound on each one; the blips can be quite annoying. Note the subtle blue bar on the left; this is just what is new since you last read the column. (You can click the check atop the column to mark all as read.)**

Now to the first column. Here you can search for names. You can also search for hashtags; that is how people gather around topics and conversations on Mastodon. I have to get back into the habit of using hashtags in my posts. If you find a hashtag very useful, you can pin it as a column that will always appear.

Click the icon with a head and many arms and you will get your “local” timeline in another column. This is just people on your server, whether you follow them or not. Depending on the server you choose, it can seem useful or random. In the setting for this column, you can choose to pin and always show it, or not. The globe icon will open a new column called the “federated” timeline, which is a collection of everything from everyone that all the folks on your server boost on other servers. It can be a firehose. You may also choose to pin or not pin this. Thus far, I don’t use the local or federated timelines much but you might like them as a way to discover serendipitous conversations and people.

Now click on the hamburger menu on the upper left of the first column. If it is not already open, this will open the “getting started” menu with lots of offerings: direct messages to you (with the caution that direct messages are not encrypted so don’t go sharing your innermost secrets here); posts you have bookmarked (I find this handy), posts you have favorited (“liked” in Twitter parlance), lists you create, follow requests (NB this is *just* the follow requests Mastodon thinks might be suspicious; you will find all your follow requests in the notifications column). Note also that you can create lists of accounts you want to read regularly — I use that feature frequently on Twitter — but unfortunately, they are private and cannot be shared. Instead, there are groups. See some examples on the academic on mastodon page.

Click #Explore and you see four nice features: Posts are posts that are popular from across the fediverse. Hashtags are stats on the trending hashtags. News is an ok list of media stories getting links. And for you are recommendations for folks to follow; I find it of limited utility.

Now, finally, to the important part: writing. In that first column, you’ll find the box for that purpose. On most Mastodon instances, the character limit is 500 — generous next to Twitter’s 140 then 280. Some servers up that to 1,000; I have so far resisted the temptation to migrate there.

Here you can add a poll and mark the post’s language. By the way, translation works pretty well; I follow people in many languages as a result.

Mastodon has many norms built up since 2016. Norms being norms, these are likely to evolve as new people arrive wanting change and veterans resist that change; such is society.

One strong norm is that when you upload an image (with the paperclip in the posting box) you are expected to click “edit” and add alt text for accessibility. I was scolded once for not doing so and now I do it.

Another set of norms revolve around the content warning. When posting, click on the CW in the creation box and you can write a small headline others will see with the option to reveal the rest of your post — or not. This was intended to mask triggering or offensive content, important because Mastodon from its start has served vulnerable communities. However, some have extended this norm to contend that the content warning should be used for political posts. Others — especially people of color — insist (rightly, I think) that we should not hide the realities of life behind this veil. How you use it or not is up to you.

Some folks prefer other interfaces for Mastodon on the web and mobile. I’m odd — Chrome OS and Android — so I can’t speak to those for Mac and Windows and IOS.

The ethos of Mastodon, I find, is friendly, polite, curious, open, caring, decent. There will be bad apples in any orchard. Block them. Report them if they’re bad enough. There are more than enough smart people here with whom to have enjoyable, informative, and provocative conversations without the trolls Elon is nurturing in the Other Place.

Keep in mind that nearly everything you do on Mastodon is thanks to the volunteers who run servers and moderate activity there. They are humans, not algorithms. They, like algorithms, will make mistakes. Give them a break.

And give them money. Every server is likely to have a link to a place to give money to the host to pay for very real technology bills. You have left the land of corporatized, centralized, controlled conversation. It’s a new and exciting world. Help support it.

**New tip, thanks to my new Mastodon friend, Maxi5X, who pointed me to the notifications setting for the quick filter bar. That’s the menu bar atop the column. Set the second choice to display all categories…

And this is what appears: 

That way, you can get notifications just for mentions, favorites, boosts, poll results, and new followers. 

That little house icon takes you to another feature I didn’t mention: When you follow someone, next to the follow button is a bell. Click on that and you will be notified whenever that person posts. Thus I see whenever Eugen and my son — and Mike Masnick — post. Cool. 

UPDATE: Here’s video of a class in Mastodon I gave to some faculty and students at the Newmark J-School. It’s essentially a video version of this post. 

Telling the story that defies telling

November 8, 2022 by Jeff Jarvis
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Jonathan Freedland’s The Escape Artist: The Man Who Broke Out of Auschwitz to Warn the World is perhaps the single most effective chronicle of the Holocaust I have read.

Freedland does not attempt to convey the full scope of the Holocaust or of Auschwitz; that is an impossibility in any literature. He tells the story of one man, Rudolf Vrba — born Walter Rosenberg — who as a teenager memorized every detail of death in the camp and became one of only four Jewish prisoners ever to escape, so he could tell the world and hope to save lives.

There are, of course, countless excellent studies and stories of Auschwitz. What impresses me so about Freedland’s is his discipline in staying close to his subject, seeing through his eyes alone — and his subject’s discipline, in turn, gathering facts.

Freedland is a journalist, an incisive thinker who, in my experience, commanded any conversation I witnessed at The Guardian, where he was head of opinion and is still a columnist. The Escape Artist is a work of journalism that I cannot help but see as a work about journalism, as it brought me to reflect on my field.

Freedland begins with the escape, then tells of Vrba’s capture, subjugation, and survival and of all he witnessed and recorded in his memory. When he manages to leave and find refuge, he and another escapee pour every fact, every number — even the sequences of numbers registered to and tattooed on prisoners and their relationship to their place of origin and date of arrival — to a committee of Jewish leaders in their home country. Their report is typed up in spare, sparse language recounting only the facts. At first, as Freedland relates, Vrba is upset that it does not include a warning to the Jews of Hungary, for based on what these two men saw and heard, they are next on the trains. The leaders refused to include anything that is not based on verifiable fact — no speculation, no prediction — to assure the credibility of the report. There is a lesson for journalism.

The report, in various versions and translations, makes its way to London and Washington and also into the hands of journalists, who finally begin to get word out about the horrors, though far too little is done. What strikes me here is the value of witness. Vrba committed a profound act of journalism; without his observation and memory and courage, there would have been no reports.

I won’t go on, only will recommend that you read or listen to the book yourself. I am going to try — and likely fail — to post more about books I am reading to share recommendations with you (and hope to read more recommendations from from).