Feminist commentary on text analysis tends to focus on the technical aspects of the work: data collection and processing, algorithms, and the visualization of results. However, most of the literature seems to start with the assumption that researchers already know how to write their research questions. Unfortunately, several case studies prove the contrary: text analysis projects that do not start with the right questions end up being flawed in all the other phases, with problems ranging from bias in data collection and inaccurate statistics to outright sexist conclusions. Research questions are at the core of a text analysis project and they influence every other phase, but there is actually little guidance on how to craft them.
In my paper, I argue that a feminist text analysis is possible and that it must start with well-thought, well-framed research questions. These must be rooted in a feminist praxis, an impetus towards action, and a realistic conception of what artificial intelligence can do.
I will create a framework to guide scholars in their formulation of research questions for their text analysis projects. To do so, I will draw from our readings from this semester, my Jupyter notebook projects, and examples of text analysis that we examined for this class. Rather than creating restrictive parameters, my framework will be a set of guidelines that feminist scholars can use to orient themselves at the very beginning of their research project, so that they can start asking the right questions.