Less cheese, more vats: A reminder that everyone’s a journalist

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For years as a “professional journalist,” I toiled away in newsrooms with my colleagues, first in front VDTs, then computers and laptops, endeavoring to tell readers what we thought they wanted or needed to know.

For the last 10 or 12 of those years, I’ve spent a lot of my time reminding my colleagues that it just doesn’t work that way any more. Yes, there’s a critical role for journalists who are trained to seek out and report news, to hold institutions accountable, to investigate. Basically, we need them to do the hard work no one else wants to do.

But the world of conventional journalism has long since been disaggregated (as has the business model; as this Nieman Lab report notes, “Politico is only about politics; Cars.com is only about cars). For newsrooms, that disaggregation is about content. There’s numerous places online to find restaurant information (thanks, Yelp, and its massive audience of contributors) and recipes (too many sites to name) and movie information (RottenTomatoes, anyone?).

All this is part of my way of introducing the direction this blog will be taking going forward. We’ll be looking at the way journalism — or at least, new forms of it — are leaving the conventional newsroom and moving into new newsrooms of a sort. These newsrooms are within the walls of corporations and brands that sell products and services to you.

They’re newsrooms that, when done well, provide sound, useful, unbiased and often entertaining information — with the hope that the consumer of the information associates the brand with reliable content.

Sometimes, the posts will be about my own observations. Often, I’ll be curating content myself on the subject of "brands as publishers” or, as it’s sometimes called, “content marketing.” What it really should be called, however, is just information.

But it goes beyond the kind of information like the recipes you’ll find on a site operated by Kraft and dedicated to its boxed macaroni and cheese product. See, the trick is, the information needs to be good. It has to be informative. It has to at least be entertaining.

It’s as simple as that.

As Contently’s James O’Brien put it in a column on Mashable, “Red Bull is a publishing empire that also happens to sell a beverage.” And they publish things like “10 Iconic Lallapalooza Moments: A walk through Lollapalooza’s past with Kanye, Pearl Jam, Lady Gaga, Pavement, The Ramones, more.”

Closer to home, consider St. Louis-based niche product marketer Vat19.com. The company markets “curiously awesome products” such as a half-gallon margarita glass, magnetic putty and beard stocking caps. Every product comes with an entertaining video. Most of them make me laugh.

Lousy content doesn’t work. Content that looks like advertising doesn’t work. I’d be curious to know whether Kraft’s site works. It’s got recipes, sure. But everyone knows the point is to get readers to buy more Kraft Macaroni and Cheese.

That’s what we’ll be looking at going forward. Fewer tubs of cheese. More vats of yummy content.

Emerging trends in social media

The “liquid self” vs. the “network effect.” Plus this: “There’s now strong interest in services that let people talk with one another in contextual environments — friends from college, friends from home, family members, and so on. These services let you communicate using the norms, expectations and relationships you have with different groups. It’s a big trend that matters a lot. Conversely, if you communicate for an organization, it’s important not to overstep bounds and become too familiar.”

Emerging trends in social media

Can algorithms tweet better than people on Twitter?

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So, apparently, I don’t know a good tweet when I see one. According to the New York Times blog The Upshot, a group of researchers from Cornell University developed an algorithm designed to predict which of two tweets would be retweeted more often.

The Times created a nifty quiz showing 25 pairs of similar tweets, and giving us ordinary folk the chance to predict which one got passed around more often on Twitter. I scored correctly on 14 out of the 25. The algorithm scored correctly on 18 of them.

I’m in good company, by the way. Marc Andreessen apparently only got one more right than I did, and I tied with Twitter co-founder Ev Williams and CBS news political director John Dickerson. (The best score recorded when I looked was 21/25 by Katie Notopoulos of Buzzfeed. Of course.)

There is hope for us mortals, according to the Times’ blog post on the topic:

That an algorithm can make these kinds of predictions shows the power of “big data.” It also illustrates a fundamental limitation of big data: Specifically, guessing which tweet gets retweeted is significantly easier than creating one that gets retweeted.

Why don’t you try the quiz and let me know how you did?