- The Search Agents - http://www.thesearchagents.com -

A Real-Time Improvement to Google Real-Time Search?

Like many, when Google announced the integration of real-time social media feed results into results for some terms, I was excited to try it out, and shocked at what I found.

Query 1: “Christmas presents”

This was a great first query to try out – lots of happy people tweeting about their Christmas shopping.  Until a result streamed by with this in the title:  ” Destroyio Records Presents O.P.S., Johnny S** F***”.  My Google SafeSearch was set to “medium” (reject images, accept text), and “Christmas” was in the body of the result, so in a way, one could argue this is acceptable, but I doubt most people would ever expect to see something with s** f**** on the first page of a search for “Christmas presents” – from a relevancy standpoint.

Query 2: “Tiger Woods”

I dutifully reset my SafeSearch setting to “Strict” and searched on “Tiger Woods”.  And watched with amazement as inappropriate joke after inappropriate joke scrolled by; some with “$$” appearing to replace “ss”, allowing some pretty “unsafe” words to sail right by Google’s SafeSearch filter.  This definitely was not what I expected.

Then I Started Tweeting...

I only have about 35 or so followers, but I thought – hey – I’ll tweet something that has the words “Tiger Woods” in it and see if it shows up.  So I tweeted the following – and it came right up within seconds (some portions redacted here – remember, this was with SafeSearch set to “strict”):

Google Real Time Search Example

It basically looks like, with a very low bar, almost anyone can say almost anything they want, as long as they use the target keyword in their post, and perhaps are creative about how they say it.  I used this example because Google had a run-in some years ago with CNET over a piece Elinor Mills wrote [1] that included publicly available information on Eric Schmidt – now any schmoe can post anything about the guy and it shows right up on page 1 of a Google SERP?  That just doesn’t seem right.  Is the world really ready for part of Google’s first results pages for some terms to be the Wild West?

How they could easily improve this

Google has a simple tool they could be employing to start addressing this – Relevance.  A posting about “Christmas presents” that contains the word “Macy’s” for instance, is probably more relevant to a query about “Christmas presents” than one that has “s** f***”.  A posting about “Tiger Woods” and “Golf” (or “Scandal”) is probably more relevant to a “tiger woods” query than one about “Tiger Woods” and “Eric Schmidt”.   Google already has great technology for determining the relevance of short text snippets to documents – AdSense – and Google uses it to match ad text to target publisher’s web pages on their Content Network.

Why didn’t they modify this technology and apply it to this problem, comparing relevancy of tweets to SERPs for instance?  It wouldn’t be perfect, but it would be far better than it currently is.   It feels rushed, and one can easily envision a wide variety of potential PR nightmares for Google.  Expect this feature to change rapidly, particularly since the time cycle for doing a test to see what gets you on page 1 of Google, for some terms, just went from 3 months to 30 seconds…it should make for an interesting arms race between spammers (and even more nefarious people) and Google in the coming weeks and months.

About Ted Ives

Ted Ives joined The Search Agency in mid 2008 and is responsible for its wide array of product and services offerings, including the agency's proprietary AdMax™ bid optimization platform. Ted previously worked for technology companies ranging through every layer of the information technology stack including APC, National Semiconductor, Apple and Microsoft. He brings great depth in product management as well as product marketing across multiple business platforms and in various types of technologies. Ted currently serves on the board of directors of FindHow, a how-to search engine startup which he co-founded in 2007. He has a degree in Computer Science and Economics from Dartmouth College and an MBA with a focus on technology marketing from Santa Clara University.