In the world of nonprofit data management, we work really hard to smart code all of our interactions with our audience so that we can successfully report on them. However, we work in a relationship industry and that often requires detailed explanation, which, translated to data speak, is free text. And there is our conundrum.
Processing free text is the domain of artificial intelligence, a discipline that we nonprofit data scientists are learning now. The new processing program, Python, even has a package called Beautiful Soup which parses websites, the text within them, and the HTML tags marking any variety of content. The R program also has a package called SentimentAnalysis which assigns a sentiment to different words by using the package’s dictionary, called a lexicon.
But we can do some of this analysis without an artificial intelligence program. Here are some steps to work your way into trying out text parsing, starting with the easy stuff and working toward the sophisticated stuff.
There was a study that I heard about years ago (and I wish I could find it now) where a suicide hotline identified through data science the keywords that indicated that the caller really meant to cause self-harm. To me, that is the best use of text analytics. Your work, since you are in a nonprofit, is also for a noble cause.
Try some of these tricks and see what you can glean from contact reports. And let us know what you find.
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