11 websites that should never, ever have a Facebook open graph read action that tells my friends what I am looking at on the Internet

  1. Gawker
  2. Deadspin
  3. Most other Gawker sites, really.
  4. Reddit
  5. TMZ
  6. Amazon
  7. Any website mentioning the name “Hunter Moore”
  8. Every alternative weekly ever.
  9. Yahoo News Slideshows
  10. YouTube
  11. Anything still hosted at a blogspot.com domain

 

Link: How to Use the “Network Density” Formula to Measure the Health of a Community

I’m a sucker for engagement formulas, especially when they help provide a means to quantitatively track something that sounds as fluffy and qualitative as “the health of a community.”

Great ideas here for community managers and related parties: How to Use the “Network Density” Formula to Measure the Health of a Community

 

Current obsessions

In no particular order…

  • Men In Blazers, a soccer podcast by Brits of some vintage, in New York City, mostly, for ESPN’s Grantland. Funny.
  • Roadrunner, by Jonathan Richman and the Modern Lovers.
  • Hay Day, an iPhone farm game. Or as we call it in my household (all members of the household, cats excluded) “the farm game” or even just “the farm.”
  • Trying to get sort of OK at, well, Rubik’s Cube.
  • Reddit.
  • Alt Latino, from NPR, because, seriously, where else are you going to hear interesting new (and old) Latin music?

Why Italy?

On Sunday, after bearing the brunt of an excited explanation of Italy’s glorious victory over England via penalties, including a stunning Panenka from Pirlo, my own wife turned around and asked me why I was rooting for the Azzurri.

This was weird, because it’s her fault.

(Hey, this is a blog post about soccer. If you’re not interested, feel free to stop reading here.)

Continue reading “Why Italy?”

2012 Civic Media Conference takeaways, open questions, reactions, notes

It’s been three years since I last made the trek to Cambridge for what we once called KNCMIT, and although the cast of characters has changed (with little-to-no representation of 2007-8-9 Knight News Challenge winners, different faces at the MIT Media Lab, and a rebooted Knight Foundation posse) the outcome was similar.

All unhappy airport terminals are alike, so the sense of deja vu carries over from the hotel to the cab to the fluorescent carpeted discomfort of Logan, and the foreboding sense of dread that comes with a United flight. (Prove me wrong, airline. Prove me wrong.)

On to the obligatory, but hopefully not exclusively duplicative and obvious notes:

  • Homicide Watch is excellent, and repeatable. Whether or not you use the code powering the DC site, the model of reporting on every homicide in a city — and not just reporting it, but reporting on it, while maintaining pages for every victim and suspect — this is something that doesn’t depend exclusively on technology, although the platform is perfectly tailored to the job. But it does depend on being obsessed with telling the stories that we often hide behind numbers, or a map. (Previously.) Also, it helps to be as driven and passionate about it as Laura, and to care about people.
  • Sometimes, there’s just no story in the data. Jonathan Stray hoisted this banner of editorial force, and Daniel X. O’Neill waved it high, the sort of basic news value that journalism school drills into us if we listen: Check the facts, check the data, then double-check it and account for the fragile chain of human actions that produced the data. Because a spreadsheet packed with invalid data and intervening variables is not a story. It’s a mess, and a risk, and it might be the start of the reporting process, not the end of it. (Session video here, worth watching.)
  • The contraction of the Knight News Challenge grant cycle into themed 90-day periods is a right and good thing, as is the new prototype fund. You should apply to one or both, right now. This minute.

Not pictured in this list: An improved opinion of the food and beverage options in Cambridge, Mass.

A future history of crowdsourced reporting

During the second or third or so year of my still-brief career in what we might as well call “the news business” for lack of a more encompassing and descriptive term, I found myself jumping up and down advocating for a tool to standardize the task of gathering data from the news audience.

Crowdsourcing as a term was new, and by definition “bigger” than just “sourcing” because it could happen at scale, where scale could be thousands, hundreds of thousands, millions of people with the right call to action and programming framework.

WNYC’s “beer, lettuce, milk” price data gathering project was a favorite, although it appears to have been powered by a comment thread, mostly.

That was always one that stuck out in my mind, due to the quantitative nature of it. This wasn’t about asking the news audience for opinions; it was a method of gathering facts about the city and its bodegas, data that wasn’t compiled anywhere, and that made sense to bring together in one place, given the chaotic system (system?) of New York City bodegas.

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Matt McAlister has gathered a Big Important List of crowdsourced reporting projects, and he’s notably compiling a list that extends beyond traditional journalism and news organizations, as we all should.

It’s a fascinating list of projects, and a reminder that it’s not always “content” news organizations are looking to “generate” from “users,” but information, or perhaps better yet, analysis of documents or images or cities or rivers or the world surrounding them.

Again, my own interest, albeit usually from afar, in tools like DocumentCloud, is the chance to bring the audience into the reporting process by giving them an assignment. “Read a piece of this giant 1100 page budget, or campaign finance bill, or FEC disclosure, or Friday night data dump (see the classic Talking Points Memo instance here), and annotate it so we can find the important stuff quickly.”

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The fun part, naturally, isn’t in examining the past of crowdsourced reporting, but imagining the future. What does a platform to quickly spin up an instance of a crowdsourcing machine when news breaks look like? More than a map, surely, as amazing and powerful as location can be. It has to be flexible and fast and able to parse submissions into something useful, digestible, sortable so the most important information surfaces as if it were weightless.

Or are we already looking at the platform, the system, in Twitter or Facebook or Google Search or the Web itself? I don’t think I believe that. There must be more, or there must be a federated system to harvest and groom information from all these sources — not for the purpose of curation into a story or list or gallery, but for analysis, understanding, quantification at scale.

Continuing to dream of that ideal crowdsourcing platform…