Methodology

I found the muga texts in the Compendium of Korean Oral Literature (한국구비문학대계). Once I collected five muga texts, I read them and tried to see if there was any gender representation in them. It was also interesting to learn about the historical objects and social norms reflected in the texts. Blinded by excitement that I would learn about the social scene during that era, I did not realize these texts contained regional dialects, possibly even from that time period, which made it hard for me to understand them. So, I used AI to convert the texts into modern versions.

Another issue was that some sentences were missing subjects, so I assigned each verb to a female or male character by looking at the surrounding context. Now, I had separate lists of sentences for females and males. I wanted to use Python to see if it could extract verbs. To do so, I asked AI, Gemini, to create a script to extract the verbs from the texts, and Python generated the lists of verbs.

Next, I wanted to understand the frequency of these verbs and how often they appeared in the texts. To achieve this, I used AI, Gemini to help write the code and ran it in Python. Then, I imported these lists into Voyant to visually see the verb frequency. Voyant displayed the verbs and offered features that showed different ways to visualize their frequency. Then, as part of this project, I created a webpage using HTML, CSS, and Bootstrap. Since I took an intro programming class last semester, I wanted to apply the skills in the project.