What @GoogleBooks’ NGRAM viewer could be . . .

A few weeks back, the @GoogleBooks team released a lab product related to the Books Project: the NGram Viewer.  According to the NGram site,

When you enter phrases into the Google Books Ngram Viewer, it displays a graph showing how those phrases have occurred in a corpus of books (e.g., “British English”, “English Fiction”, “French”) over the selected years.

In short? Put words or phrases into the search box, separated by commas, select a time range, and the NGram viewer displays the frequency at which each appears in the corpus of text contained in the Google Books database.  A few quick searches, with predictable results, that I did when I first experimented with the tool included: (a) groovy, (b) laptop, and (c) hillbilly.

My question, “Where does @GoogleBooks plan for this project to go in the future? And, do they realize this could be a killer app for qualitative research?”  Imagine two things.

First, rather than only laying the tool over the top of the Google Books database, enable it’s use with any database; in particular, I’m thinking in terms of a research database that contains the texts and transcripts of interviews or other qualitative research data.

Second, add algorithms that flip the search function around; rather than user input dictating the results, develop algorithms that identify the most used words *and/or* phrases.  If you’re familiar with Wordles, think something similar to what Wordle.net does but with the added feature of identifying phrases and not just individual words.

The results could be an invaluable starting point for qualitative researchers with large quantities of data.  NGram used in that manner would identify for researchers the most frequently used words or phrases which takes a significant step toward identifying recurring themes across artifacts whether it be interview transcripts, texts, or documents etc.