Confession: Data mining was not something that I was particularly drawn to before attending this workshop. I was unsure of the relevance of data mining to my research questions, and I was highly skeptical of the validity of projects that are premised on mined data. Today I was thrown deep into the data mine.

I wish I could say that today’s session was converted me to the glories of data mining, but I am afraid that I came away with more skepticism about how this can be useful to my research. While it was interesting to use Voyant to analyze texts and Google N-Gram to evaluate the changing use of word usage, I am still hesitant to embrace the validity of such findings. I think that these tools provide an interesting glimpse into texts and the visualizations of this data may even be very compelling, but I am not sure that those findings can be the end of the argument. In fact, I think the greatest appeal of these tools (as far as I can tell after one day in the field of data mining) is that the data that is revealed through these processes raises more questions, the visualizations ask for the inquiry to reach deeper.

Heading back into the data mine for Day Two. I hope I survive.

Source: Canary in the Data Mine