All the major search engines have recently incorporated real-time search results. For example, blogposts that used to take 5-15 minutes to get indexed are now under 10 seconds (see video at http://www.technologyreview.com/video/?vid=513).

However, Google claims to be the most complete by incorporating blogs, news headline scans, and social network feeds, including Twitter posts (tweets). Now, bits of the formula are being revealed as to how such results are sifted and ranked, thanks to a recent interview with Google Fellow, Amit Singhal (http://www.technologyreview.com/web/24353/page1/):

- Tweets by more-followed users get higher reputation scores, and the halo effect extends to posts by those who are followed by any popular users, even if they themselves have few followers. "One user following another in social media is analogous to one page linking to another on the Web. Both are a form of recommendation." And as we know, pages with a lot of inbound links tend to get ranked higher on search engines!

- While hashtags are useful to maximize tweet exposure, "they can also serve as red flags to lower tweet quality and attract spam-like content." Google's real-time search model supposedly reduces exposure low-quality tweets with hashtags.

- Google also claims its algorithm sifts through noise tweets (e.g., when searching for "Obama," if there's a wave of tweets and blogposts about "Cambridge police" or "Harry Reid" near mentions of "Obama", those results show, rather than tweets from the White House press releases team).

So what's next? Things like tweaking real-time search results using geolocation data "which can be added to postings sent from smartphones."

While Twitter is "a very important component of the real-time Web," Singhal said, "there's a lot of value in news, blogs, and Web pages that are being generated in real-time, because news organizations work very hard to get quality to a certain level."

HOW DOES THIS IMPACT YOU?

First, from a sourcing perspective: If the highest-reputation people are the ones whose posts appear atop the real-time search results, then it's reasonable to conclude that these are the popular influencers that you'll want to have in your referral network, even if they're not candidates. So it helps you a bit to prioritize to whom to reach out. Also, you get real-time data that can feed competitive intelligence. It should be feasible to create a Google Custom Search Engine and/or Google Alert that would allow you to flow the latest information to your team. Finally, if geolocation data is being added to (and considered in presenting) results, it wouldn't surprise me if mashups started emerging that, say, let you map talent among the search results by location.

Second, from a recruitment marketing perspective: Now we get a window on what leads to highly-ranked real-time search results. So if you're trying to get your company noticed by passive talent, you'll want to get connect to (and get followed by) luminaries in your talent target space, get those people to comment on your team's blogposts, go easy on the hashtags, and post comments to (or get mentions within -- ideally with links, in either case!) relevant articles posted by high-legitimacy news outlets. For more advice along these lines, contact experts on SEO-SEM for recruiting like Nicole Bodem (http://aces.arbita.net/nicole).

The above are my preliminary thoughts on the possibilities and surely not an exhaustive list. I'd love to hear how you think real-time search may impact your sourcing and recruiting as well. Email your thoughts to me at glenn at arbita dot net and I'll be happy to credit you in a future Arbita whitepaper on this topic if we can use your material, but we'll give you a free copy of the report, in any case!

P.S. In a post about another Google search advancement (http://www.technologyreview.com/web/24082/page2/), its "visual search tool, released in Google Labs, lets users take a photo of a landmark or a store sign, for example, and then searches billions of images for matches, and for Web pages providing relevant information.... However, this feature will not include face-recognition software until Google devises a system to protect privacy." But another public search engine has beaten Google to the punch! See Shally's recent blogpost about TinEye at http://aces.arbita.net/blog/tineye-reverse-image-search-finding-peopel-based-logos-they-use (pretty good for a free tool).