STATISTICAL TRENDS IN ONLINE ANTI-FEMINISM AND THE 2022 SOUTH KOREAN PRESIDENTIAL ELECTION

Abstract

This thesis investigates statistical trends in online anti-feminism discourse in South Korea surrounding the 2022 presidential election, which saw the victory of conservative candidate Yoon Suk-yeol amidst a reported rise in anti-feminist sentiments, particularly among young men. By collecting data from YouTube videos and comments using the YouTube Data API, a dataset spanning March 2020 to March 2023 was compiled, containing over 1,300 Korean-language videos and 41,000 comments related to feminism and anti-feminism keywords and phrases. The videos and comments were analyzed across several metrics, including view count, like/view ratio, comment/view ratio, and negative sentiment of video titles and comment text. Google's Perspective API, which specializes in toxicity, was used for sentiment analysis. Statistical correlations between these variables and time were examined, with particular focus on potential changes around the March 2022 election date. The results reveal a statistically significant increase in average negative sentiment expressed in the titles of anti-feminist and feminist videos over the three-year survey period. Several other significant findings include an increase in average like/view ratio over the same video dataset for the three-year period, indicating a potential tangential increase in polarity on the issue, as well as a rise in average negative sentiment in aggregated comment text over the six-month period leading up to the March 9th, 2022 election date. View count and comment/view ratio were found to have limited correlation with the analyzed time windows. While limited by a relatively small sample size, the findings point towards increasing toxicity and potential polarization in Korean online discourse surrounding feminism and anti-feminism. This aligns with reports of an emboldened anti-feminist movement that may have contributed to Yoon's victory. The paper establishes a framework for further research using larger datasets and other social media platforms to better understand this evolving socio-political phenomenon and its impacts.