Where has been controversy, it's been primarily about how to parse documents rather than whether to parse them during a particular piece of research.
By far and away, qualitative analysis has always been the most common method for dealing with company documents. Researchers examine the documents in a more or less formal way and look for themes, attitudes, values, whatever in a more or less systematic manner. The main problem with this method is that it opens the door to unrecognized biases and subjectivity as the project continues.
Quantitative analysis has been used much less frequently. On the one hand, it's long been recognized as a powerful method that can uncover important information that is overlooked by qualitative methods. It can also neutralize sources of biases and subjectivity. On the other hand, it has historically been very expensive and time consuming, since it requires considerable coding and categorization and scoring to generate its reports.
In a practical situation, then, the cultural analyst had to choose between a method that was relatively quick and inexpensive or one that was more difficult and expensive.
Now that situation is changing as the technology for mining "big data" becomes increasingly available to many different kinds of organizational researchers.
A good example: Adam Liptak - reporting about Supreme Court opinions - talks about a new "cottage industry of quantitative analysis of Supreme Court opinions using linguistic software."
Some points made in Liptak's summary of a recent content analysis study:
- Opinions are getting a lot longer. "Citizens United, the 2010 campaign finance decision, contained 48,000 words. That is roughly the length of The Great Gatsby."
- The new study, like earlier ones, found evidence that law clerks do much of the writing at the Supreme Court.
- Some evidence suggests Chief Justice Roberts and Justices Scalia and Breyer are more likely to have written more of their own opinions.
- Justices Samuel Alito Jr., Breyer, Kennedy, Scalia and Thomas are really grumpy.
From our perspective, we can frame this story as an example of how we can develop better methods of illuminating organizational culture in the practical world in which many of us operate. We've long known that we needed an easier way to quantitatively examine documents in practical settings but we've never had the tools to do this quickly and cost effectively.
Now those tools are becoming visible on the horizon. The software needed for such work is readily available in academic circles and will become increasingly available to other kinds of users.
I'll be slowly posting on developments in this area over the next few months, so come back and visit once in a while to see if there's anything that might help you hone your skills.
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