One of the biggest challenges in covering the unrest in Egypt — or, for that matter, in covering any event that’s in some way “foreign” — is determining who can provide relevant and accurate news about the event. To curate content is in large part to curate expertise; faced with a frenzy of news updates — some of them true, some of them false, some of them in-between — how do you know which updates, and whose updates, to listen to? How do you know whom to trust?

Sulia, a NYC-based startup, has made it a point to figure that out. Using a combination of crowdsourcing, human editorial insight, and machine learning, Sulia creates topic channels, somewhat akin to news verticals, whose content is curated from experts in particular subjects — both broad (tech and science) and narrow (Ruby and Ruby on Rails), both of historical import (the protests in Egypt) and not so much (bacon). Think of the channels as megalists (or, more accurately, metalists): composite lists consisting of the most authoritative members of constituent lists.

Sulia is built from a simple insight: that membership on a Twitter list is essentially a vote for topical expertise. If someone puts me on a list about, oh, I don’t know, Jersey Shore, they’re saying, basically: “That Megan knows her Snooki.” They’re highlighting, and leveraging, the kind of topic-specific — and topic-relative — authority that the web, with all its nooks and niches, tends to be good at teasing out.

They’re also, to an extent, doing Sulia’s work for it. And that’s an important efficiency. Sulia makes use of “passive crowdsourcing,” says Josh Young, Sulia’s VP of Editorial and Expert Operations. It harnesses actions Twitter users have taken voluntarily, cognitive surplus-style, and repurposes them: as data sets. Which, in turn, become authority metrics. Which, in turn, become curated editorial content. (Sulia, in its content-curation-by-way-of-authority-determination, is similar to The Hourly Press, Lyn Headley‘s “News about News” tool that we use here at the Lab for, among other things, creating our “popular on Twitter” posts.)

For Sulia’s coverage of the protests in Egypt, its human-meets-algorithm editorial filtration has led to content — reporting and analysis — that’s essentially pre-vetted for relevance and accuracy. Sulia, formerly TLists, uses the TLists engine to crawl more than a million Twitter lists, identifying, in the process, the most respected sources on Twitter. (Sulia has a close relationship with Twitter itself, and uses its API.) To create its Egypt channel — which, like its other channels, is constantly being updated and refined — Sulia didn’t need to start from scratch to identify relevant experts; instead, Young told me, its team simply took mashups of relevant, related channels. “We already knew who the most socially respected Egyptian tweeters were,” Young notes; creating an authoritative channel was simply a matter of merging lists and then running them through editorial filters.

That baked-in contextual insight — Sulia’s proactive, pre-existing knowledge of Egypt experts — is key. While many in the media had to scramble to answer the whom-to-trust question when Egypt’s protests began, Sulia had already done that work. Locating authority was simply a matter of merging: a few easy mashups. We talk about “parachute journalism” when it comes to reporting — generally, of course, in order to be dismissive of its obvious drawbacks. But the drawbacks are just as obvious when it comes to parachute curation. Particularly as crowdsourcing becomes increasingly common — which is to say, as economies of scale change the value proposition of traditional journalism — there’s a lot to be said for an editorial framework that makes vetting the point.

And there’s a lot to be said for the vetting of content itself. Sulia, both algorithmically and through human editing, filters off-topic tweets to provide users with topic-relevant content in real time. It weeds out the “here’s what I had for breakfast” tweets to get to the topically relevant stuff. (So if I’m on that list of Jersey Shore experts and make it onto Sulia’s list…you’ll get only my profound thoughts on the antics of The Situation, not any thoughts I might have about, say, news innovation.) And that’s important. One of the drawbacks of lists, at least as I’ve seen it, has been their holistic quality: Lists, in general, have a single focus. But people, in general, are multi-dimensional. That leads to a lot of topic irrelevance in traditional lists: some signal, sure, but also a lot of noise.

Sulia combats that. And, in that, it shifts lists’ value proposition: They become less about the people populating them, and more about the content they produce. They turn expertise itself into an editorial product, transforming lists — simple, raw — into channels. In the case of Egypt, they create a place users can go to get real-time updates on what’s going on — filtered, vetted, and direct from the experts.