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Beyond TigerPlan, I have many other experiences with code, problem-solving, and data analysis.
TL;DR: Code. Lots of it.
For my Junior Independent Work, I was fortunate to complete a project under the supervision of Brian Kernighan, titled "Analyzing YouTube Comment Sentiment, Post Dislike Counter Removal." In this project, I analyzed data from 500 YouTube videos, which included millions of comments, to understand how the removal of the dislike counter impacted viewer sentiment. Utilizing the Natural Language Toolkit (NLTK), I conducted sentiment analysis to assess the emotional tone of the comments, providing valuable insights into audience reactions and the broader implications for content creators in the evolving landscape of online engagement. This experience not only enhanced my analytical skills but also deepened my understanding of user interaction in digital media.
My findings indicate that overall positive sentiment in YouTube comments increased following the removal of the dislike counter. While most genres experienced a rise in positivity, exceptions were observed in the gaming and shopping categories, where there was a stronger negative sentiment. These results highlight how the removal of the dislike counter has not only affected sentiment but also reflects broader implications for moderation and user engagement on YouTube.
In two of my