Mapping…what exactly? Google Insights for Search
August 16, 2008
By allowing you to visualize the google search history for a given term across a few geographic and temporal dimensions, the tool lends itself to some wonderful applications – including this one – a glance at social networking around the world by a Swedish firm named Pingdom – which inspired Ethan’s post in the first place.
As Ethan points out, though, the search insights data also provokes a question about what it means to search in the first place (my emphasis):
The Insight data isn’t measuring traffic to those sites, or their number of active members, just the number of folks searching for those sites via Google. That may or may not be an effective proxy for interest in those networks. I’m a Facebook user, and I have the site bookmarked, so I rarely would find myself searching for the site – it’s possible that the search data is a more effective proxy for the strength of a brand in a particular market, or the level of interest from non-participants in a specific site
I had a good time playing with these theories by using the comparative graphing features to consider where different political blogs attracted a greater relative volume of searches. Sorry the maps display a bit small, but you should be able to download the files (or simply re-create the search) to get a closer look.
Here’s a fun, obvious one:
(note: the data is also normalized in relation to the highest value occurring within the query range).
Check out how they both spike after the 2004 election, but then the relative volume of searches for Kos stay consistently higher (peaking after the 2006 mid-term elections) than those for Insty.
Make of that what you will. I wouldn’t even hazard a guess without knowing more about the reasons people turn to the Internet (and Google) to find political information.
I think the story gets even more interesting when you compare the high traffic states for each blog.
And here’s Kos:
If you ignore the ratios for a second and just focus on the states in each list:
- Instapundit: DC, TN, NH, VA, MD, KS, NC, NY, WA, CT
- Kos: VT, DC, OR, WA, NM, MT, ME, NY, WY, CA
Once again, extrapolate at your own risk. All I know is that it does not track perfectly with voting patterns and that the overlaps (DC, NY, WA) are at least as interesting as the extreme mismatches (WY, VT, MT).