I understood text mining as a concept, using Voyant, with all its highs and lows, helped my comprehension. I realized my knowledge was thin, familiar with word clouds and graphing, working with Voyant, and I am curious about other tools as well now, I was able to delve into the context, and found some surprises.

Sinclair and Lockwood discussed the two basic questions for text mining:

• a means of taking linguistic and semantic characteristics and seeing the different uses and context
• taking unfamiliar work and making it understandable

The experience I had exploring the Kentucky dataset supports the idea. For Kentucky, I ended up with this cirrus

 

The prevalence of the word “War” surprised me, until I dug into the context. War was discussed as part of the story of participants, in the context of the Civil War, and as a verb. War, it turned out, also meant was. Simply looking at the word cloud or even the trends, would not have shown the other meaning, and just left it as the interviewees must have been deeply invested in the war.

 

Voyant was a little challenging sometimes, with functions working some times and not others, but the value of the tools outweighed any issues with the program.

The text mining exercise was interesting and made me think more about what can be learned, and how little I knew at the start.