As I wander through the massive ALA exhibit floor I’m always on the lookout for new and interesting vendors I’ve never heard of before. There’s usually a few, particularly those hawking some new technology. One that caught my eye in Anaheim was ChunkIt!. ChunkIt! is a search engine, but the idea is to use it to refine searches that you conduct on other search engines, like Google or Yahoo, or even library databases like EBSCO, ProQuest or LexisNexis. ChunkIt! basically lets you refine an initial search by adding an additional word or phrase, and then it presents the results in a split screen with the original results on the right and the ChunkIt! results on the left. Now this can actually provide some interesting results with search engine output.
So being an inquisitive librarian I went to the booth representative and got my brief demo and allowed myself to be signed up as a ChunkIt! beta tester. When I got back to work I had an email message waiting in my inbox telling me how to get started with ChunkIt!. Once I had installed ChunkIt! I experimented with some Google searches and it actually did some pretty cool stuff. For example, I searched my name in Google and since it is so common I get tons of results. Then I typed “keeping up” as a phrase in the ChunkIt! search box and I quickly narrowed the search results to just those items about myself and my keeping up resources (great vanity searching). At the ChunkIt! booth a primary selling point for librarians was the ability to use ChunkIt! on library databases. I wasn’t so sure about how well that would work or if it was even a good idea given the many search refinement features built into the typical library database.
I quickly received another email from my new friends at ChunkIt! telling me I could learn more about how to use it by examining some of their cool videos. So I did. Here’s an interesting one. It follows a student with a tight deadline to get a research paper done. Take a look.
Let’s breakdown this helpful video.
First of all, would any academic librarian recommend using LexisNexis Academic for research on the russian revolution? So that’s the first reason a student should ask a librarian for help. Using the wrong database for your research is usually the first step in an unpleasant research experience. Realistically though, raise your hand if you think the student would go right to Wikipedia.
The video continues to do a good job of demonstrating why students can really benefit from asking a librarian for help. Wouldn’t it be so much easier to just type “lenin” into the box right on the LexisNexis results page that says “search within results”. Why would you go to all the trouble to do the exact same thing with ChunkIt! when LexisNexis has already built that feature right into the database? But you knew that. The folks who made this video obviously didn’t talk to a librarian before writing the script. Furthermore you can do cool stuff in the LexisNexis “search within results” box like ATLEAST3 to quickly narrow to articles that mention Lenin three times (much more relevant than those that mention it one time) or LENGTH>500 (a longer article usually has more substance).
And another thing they didn’t realize is that LexisNexis is the original text chunker. We call that KWIC output. Yes, you don’t have to look at the results in list format. Just drop the “show” box and change the output format to KWIC and voila – you’ve got chunks of relevant text.
So while ChunkIt! may have some useful applications for search engines that offer no useful features for search refinement, it may not work as well for library databases that do offer a nice range of methods for students that do need to quickly move from very broad to more narrow results. That’s the whole nature of search. The challenge for academic librarians is educating our user community to be aware of these features until such time as the technology and interfaces make them simpler to find and use. But in the meantime, I think there is a good use for this video. Why not show it in library instruction sessions as a good example of why it’s a bad idea to wait until two hours before your paper is due to start your research when you can ask a librarian for help the day before.