The issue we have been addressing all semester is “Can there be such a thing as feminist text analysis?” Our readings give us the theoretical basis for this discussion and the notebooks give us practical skills in text analysis, so we understand how difficult it is in fact to practice what we learn and talk about. The gap is drawing a closer tie between the theory as we understand it, and the reality of applying those theories. Looking at the steps as laid out by Nguyen et al (Research questions, Data, Conceptualization, Operationalization, and Analysis) I propose that we look carefully at the iterative and narrowing process that occurs when we start to operationalize our research.
The ready-made tools in the NLTK don’t allow us to work easily with the multi-variant, non-binary nature of intersectional data, so we make decisions to narrow our process and thus the research question.
I argue that these tools are not magic, they are built by men and can be disassembled and reassembled by feminists. Broussard warns us against technochavanism, to not resign ourselves to the current trajectory of available analysis tools. I plan to look at some specific tools/functions in use to make recommendations about how they can be improved to be more transparent.
As the newest crop of Data Visualization and Digital Humanities scholars, it is up to us to create new metrics, new tools for measuring, new ways to visualize results.
Nguyen, Dong, Maria Liakata, Simon DeDeo, Jacob Eisenstein, David Mimno, Rebekah Tromble, and Jane Winters. “How we do things with words: Analyzing text as social and cultural data” arXiv:1907.01468v1 [cs.CL] 2 Jul 2019.
Broussard, Meredith. Artificial Unintelligence: How Computers Misunderstand the World. The MIT Press, 2018.