How recruiters can source great candidates by analyzing Twitter's hidden networks

Looking for awesome job candidates? By analyzing who key people within a target industry or business follow, Twiangulate helps recruiters identify highly-value, passive candidates.

This blog posts shows how just ten minutes of digging can reveal hundreds of potential job candidates on Twitter. As you'll see below, this can be done even inside a notoriously insular company like Apple.

Twitter is clearly loved by many recruiters. But most recruiters' Tweets are stuck in web 1.0 -- the broadcast era. When trying to connect with job candidates, these recruiters use Twitter as just another channel for blasting out job openings. A few recruiters up their game by tweeting about their companies' uniformly awesome corporate cultures. Some even use #hashtags so their tweets are seen by potential hires interested in specific content.

And a few recruiters, the really advanced ones, have figured out how to use Twitter advanced search to identify people interested in specific content or working in a specific company.

But this is just scratching the surface. Twitter's social graph, aka 'who follows who,' contains a treasure trove of information for smart recruiters. Twiangulate can help recruiters expose the hidden networks of influence by analyzing who is followed by people within a particular field or organization or company unit.

For example, let's say you desperately need to hire an iCloud programmer with experience at Apple.

The first step is Twiangulate's bio search. Putting "iCloud" into the search quickly yields up 262 names. Scanning the list, @ThomasHan quickly jumps out. He works in Cupertino and his bio says: "Taiwan. Purdue. Cornell. Apple iCloud Engineer. Husband. Charlie, the doggie. Views and opinions do not represent those of my employer."

"Apple iCloud Engineer" sounds promising. The traditional recruiter would try to get into a conversation with Thomas Han, perhaps get him on the phone and see if he knows any Apple colleagues who might be looking for a job. But Twiangulate let's you turn @ThomasHan's Twitter connections into the decoder ring that produces a list of several hundred programmers at Apple.

How? Your next stop is Twiangulate's "reach" tab, which lets you review @ThomasHan's most influential followers.. This search yields a snapshot of Han's 100 most influential followers. Turns out Han DOES have the ear of a bunch of hefty Tweeters both inside Apple and outside, confirming that he might be a good person to try to hire. But this list yields more: the names of other Apple staff.

Twiangulation for recruiters

It turns out two of Han's influential followers, @eschaton and @espresso, list Cupertino, home of Apple's HQ, in their bios. Grabbing their names and switching over to the "followed by" tab, we can now do a search that discovers all the tweeters who @thomashan, @eschaton and @espresso follow in common.

Bingo, we've now got a list of 302 people, many of whom are current or former Apple programmers.

And swapping some of these names into the same 'who do these people follow in common?' search function yields even more candidates. Now add all these names to a Twitter list, for example, Great Programmers We Want to Hire. You've located a Fort Knox of well-respected but behind-the-scenes Apple staff.

Who does Congress follow?

Who does Congress follow? Dan Amira and the New York Magazine Intelligencer team did a lot of good digging into a pile of Twiangulate data a few weeks back.

The usual suspects @thehill (followed by 62.9% of Congress), @politico (61.2%), @cspan (61%) and @rollcall (59.9%) were most followed. The big surprise came in the strong showing of the success of @mikeallen, who tied the venerable @washingtonpost at 53.3%.

How Twiangulate measures reach

Instead of relying on complex, secret “influence” algorithms like Klout and Peer Index, Twiangulate measures influence as reach, the number of people who follow a tweeter's real biggest followers.

When calculating biggest followers, Twiangulate only includes people who might actually read tweets. We exclude mega accounts that follow more than 11,000 people or with a friend/follower ratio below 1.5.

That’s real clout, right?

Trying too hard in your Twitter bio?

Here's a list of overused words in Twitter bios that fail by telling rather than showing. Click the words below to see who uses each in Twitter.

Expert or Maven (33,209) It’s up to your peers, not you, to declare you an expert. Too often, seeing "expert" in a bio sends us running in the opposite direction. Kinda like being a self-described "winner."

Guru (14,309) Nothing shouts "leader of a cult with one member" more than a self-titled "guru." Unless you're a yogi or a certified leader of Eastern religion, leave the Guru-ing to, you know, Gurus.

Social Media (44,518) If you're a "social media" strategist, chances are that your intended audience is full of other "social media" types. And they don't call it social media, they just call it "work."

Enthusiast (39,237) Enthusiast sounds sweeter and less pompous than guru or expert. It's just that, well, lots of other people are enthusiastic about being an enthusiast. How about "fan?" Or, if you're just trying to say it with more syllables, try "aficionado."

Nerd (31,052) Back in the day, "nerd" was an inflammatory word that conjured up images of taped-together glasses and greasy hair. Today, "nerd" can be synonymous with "enthusiast," both in meaning and frequency of use on the internet.

Geek (68,754) The debate has raged over the differences between nerds and geeks since Sputnik. This venn diagram indicates a geek is a nerd with social skills. There are a lot of networked nerds out there.

Human or Person (128,109) It may feel sensitive to finish off your bio with "human" or "person." But your writing should prove you're not a robot.  If your bio says "father, skateboarder, guitarist, social media guru, cyborg," THEN we're excited.

2.0 (13,711), Interactive (12,179), and Online (103,349)Do you add "Earth" to your mailing address?

Don't despair if you're using some of these words or phrases.  But if you're using two at once -- for example Social Media Enthusiasts (2791) or Expert Gurus (470) -- do some pruning.

And if you're using three -- Online Mavens of Geekdom -- hire a human.

Bonus: There are 8901 ninjas on twitter. Who's minding the dojo?

For more fun with buzzword (ab)use, check out LinkedIn's most overused profile buzzwords.

Mapping Twitter activity during the Egyptian revolution

"In a case of ironic symbolism, the far left-most satellites are the Whitehouse, State Department, and Wael Ghonim's employeer, Eric Schmidt, who is merely a speck on the map. And that's probably how everyone in the rest of the network would like this future to look. " See the map here.

LinkedIn adds connection mapping for member profiles

LinkedIn's new service is very cool, allowing a user to label the various groups she discerns among her contacts. The cluster mapping was, as far as I could tell, very accurate. Here's the map for Henry Copeland.

Wikipedia social network analysis discovers hierarchies

"Early results may indicate that Wikipedia isn’t as communal, egalitarian and free of division of labor as thought. Hierarchies featuring bosses and workers, elites and the not-so-elite, have developed. This may, in fact, be necessary when humans organize to produce something as complex as an encyclopedia, despite the essentially democratic nature of network technologies that can, theoretically, allow anyone to participate equally." Plus cools maps and descriptions of code/hardware. Social network analysis of Wikipedia.

Twitter trending topics: say you want a revolution?

Are Twitter users idiots who can't spell John Lennon's name right?

No doubt some of them are dumb enough to spell it "Lenon," which is currently listed as a trending topic.

In fact, "Lennon" seems to show up at least five times as often if you run simultanous searches of Lennon and Lenon.

So it appears that Twitter's trending topic algorithms ignore "Lennon" because the name of the greatest Beatle already shows up thousands of times every day of the year. In other words, the machine thinks Lennon isn't news. Clearly some tweaking needed.

This seems to parallel the situation with the nontrending Wikileaks.

Update: here's a good analysis of the Lenon/Lennon problem, concluding that "But it’s important to stop at this point and note that even though the reasons are understandable, they still make absolutely no sense."

How to find people on Twitter

There are two easy ways to find a person on Twitter, even when the person is not using her/his exact name as a Twitter ID.

First, you can use Twiangulate's "keyword" search for the person's name. Here are 53 people who are identifying themselves as "Lucy Smith" on Twitter.

If this method doesn't work, try to think of two or three people who might know the person you're looking for and then input their names into Twiangulate's "common friends" search.

For example, if you're looking to follow Elizabeth Spiers, Gawker's first editor, you might look for her among the friends of NYC media insiders like David Carr (@carr2n) and Gawker (@gawker) and Anil Dash (@anildash.) Sure enough, she's right there.

Twitter mapping

Want to map the relationships among a bunch a tweeps? It's really quick and easy. (Works best with <100 tweeps.)