Methodology

My Data

In this class we used Python and AO3 Scraper master from Github to obtain a corpus of fanfics to analyze and perform statistical analysis on. It was important to scrape the correct corpus of data to represent what you are looking to answer with your thesis. Since I chose to focus on the role of canon in the ACOTAR fandom through an analysis of differences in character popularity and Azriel more specifically, I had to scrape data from AO3 twice. After some initial complications scraping all 7000+ fanfics, I asked for help to scrape some of the most recent fanfics to act as a data set to analyze who people are writing about recently. This first sample was collected on December 5th 2022 at 10:30 AM and consists of 2876 out of about 7250 fanfics. This data acted as my main set and was used in Gephi, as well as to compile several timelines of different characters' appearances in fanfic. This meant this data set had to go through lots of cleaning in Excel to produce accurate results. I used this data to perform all of my initial data analysis until I realized I wanted to look further into Azriel individually.

After Gephi revealed that Azriel was more popular than Feyre in the initial sample of data I once again used the same methodology of AO3 Scraper master and Python to retrieve the metadata for the 1000 most popular ACOTAR fanfics with Azriel listed as a character. I scraped this data set by first filtering on AO3 for fanfics containing Azriel, then sorting it for most popular by kudos. I scraped on December 7th at 12 AM and included a filter to only retrieve 1000 fanfics in English. This data set revealed more about why people might be writing about Azriel, despite him not being a main character in any of the books yet. I used it to analyze his character popularity over time as well as to look at ratings on AO3.

Tools Used

Python

Excel

Gephi

Tableau