Our web search strategies are largely unconscious. Back in December I dredged one up to take a look at it, and resolved to do that again from time to time. Today’s challenge was to find this article on infomania that I read about a week ago and neglected to bookmark. More specifically, I needed to recall the name Mary Czerwinski, a Microsoft researcher mentioned in the story, because I want to interview her for a podcast.
The multi-step strategy that got me there is subtle, and independent of any particular search engine. Here were the givens:
- I thought I’d seen the story on SeattlePI.com.
- I thought the researcher was female, and was an organizer of the event that was the subject of the story.
- I thought I’d recognize her name if I saw it.
- I thought that the word “attention” would appear frequently in the story.
I started with these queries:
“microsoft research” conference on attention
“microsoft research” seminar on interruption
This would have nailed it:
“microsoft research” workshop on infomania
But of course I didn’t recall that it was a workshop rather than a seminar or conference, and the word infomania hadn’t sunk in when I read the article.
Next I tried this:
“microsoft research” “continuous partial attention”
This leads, in any search engine, to Linda Stone, which I knew was a blind alley. I’ve read and heard Linda Stone on the subject of continuous partial attention, I know she’s no longer at Microsoft and wasn’t the female researcher in the story. But I figured this query would get me in the neighborhood, that the nimbus of documents surrounding her name would shake something loose. It didn’t.
Next I broadened to:
“microsoft research” attention
This leads, in any search engine, to Eric Horvitz. Note that although Eric Horvitz’s name does appear in the story I was looking for, the word “attention” does not appear in the story.
I wish I could be more precise about what happened next, but the general idea was to explore documents surrounding Eric Horvitz that would contain the name of a female researcher which, when I saw it, would ring a bell. In a couple of clicks I saw the name “Mary Czerwinski” and it did ring a bell. So my final search at SeattlePI.com was for Mary Czerwinski, and the target story was the first hit.
In retrospect I could’ve searched SeattlePI for Eric Horvitz and found the target story as the second hit. I can’t say exactly why I didn’t, but I suspect it’s because I thought exploring the document cluster around Eric Horvitz would be useful for other reasons than to locate Mary.
We perform these kinds of searches every day without thinking much about them, but there’s an amazing amount of stuff going on under the hood. Consider, for example, the aspect of this strategy that involves switching from general search engines to SeattlePI’s search engine. If I was right about the the source of the article, that would be a winning strategy because the target would tend to pop up readily in SeattlePI’s engine. If I was wrong, though, it would be a complete waste of time. Some part of my brain calculated that tradeoff. A successful search strategy involves a bunch of those kinds of calculations. How could we surface them from unconsciousness, study them, and optimize them?