Quick & Dirty Qualitative Analysis

So I’ve been thinking on ways in which nonprofit organizations might be able to take lots of text from reflections, surveys, testimonials, and other such word heavy data and quickly code the data for analysis.  Over the last six months, the 119 Gallery (http://www.119gallery.org) has been conducting a survey (https://docs.google.com/spreadsheet/viewform?pli=1&formkey=dGg2Smk1b0VqbEhfTHNRVUxfWFlNVlE6MQ#gid=0) on impacts members of its creative community have experienced from the gallery.

I took all of the text from the 44 responses and pasted that text into Wordle (http://www.wordle.net) which is a free tool to create word clouds.  The only word I deleted from the text was “gallery” since it is used often in reference to the name of the space.  Here is the resulting Wordle:

So initially, I would say that this display of text data is a good first step to assessing raw word count content.  In reading the responses it was clear that the sense of community was clearly present and given that the organization is an arts organization it is therefore not surprising that the 119 emerges as a “community art” space.

People, artists and Walter (one of the founders) emerge as other prominent words.   The what of the space — work, shows, events, music are not surprising.  The ideas of support, appreciation, welcoming are joined by open, creative, opportunity and unique which are in my opinion essential qualities of the organization.  Other interesting words that emerge are things like sense, felt, believe, feel and experience.

What the quick and dirty doesn’t provide is more nuance and context to the words.  Thus a traditional coding process can get at deeper meaning.  But this initial test seems promising.