About
Sources
To understand Twitch performance analytics more comprehensively, we used a dataset sourced from twitchtracker.com. The site ranks the top 1000 Twitch streamers in real time by averaging a creator’s follower count, view count, stream time, and other factors, which became helpful for us in providing a metric used to assess success on Twitch.
For understanding social constraints to creators’ success on Twitch, we referenced studies on labor, identity, and online community formation within livestreaming culture. These revealed how visibility is often shaped by external factors such as gender expectations, language dominance, and algorithmic favoritism. Factors that propelled success on the platform, as discussed by scholars of digital labor and parasocial engagement, revealed that sustained visibility often comes from consistent content production, emotional connection with viewers, and strategic use of platform tools.
Processing
Due to how the original scraper organized the TwitchTracker data, the dataset we worked with was already well-structured. Before exporting the CSV file to Tableau for visualization, we first imported information into Google Sheets to reformat and clear out small discrepancies, including standardizing game titles and removing missing rows. While we didn’t do any intricate statistical processing, we concentrated on preparing the data for display, keeping in mind the significance of “getting data ready for cleaning,” making sure that formatting decisions would skew meaning (Data+Design, pg 100-116).
We created charts using Tableau to highlight the platform’s apparent trends across games and streamers. Tableau was used because of its ease of use and efficiency in making interactive graphics, which are needed for iterative storytelling. Timeline.js was also used to show how Twitch evolved into the streaming behemoth it is today. With the use of this website, we were able to combine comments and images, giving us normally static data with added narrative meaning. Effective visuals start with careful formatting, not merely design (How to Get Started in Data Visualization, p. 2). The reminder in Turabian that all research decisions, including technical ones, contribute to a wide argument and should be made with rhetorical awareness also affected our processing choices (Turabian, pg 6-7).
Presentation
Since our research focuses on Twitch and the broader gaming industry, we wanted our website to reflect a gamer-oriented aesthetic that feels authentic to the culture we’re analyzing. Visually, we drew inspiration from Twitch’s signature purple (#4B0082) and paired it with complementary bold tones to create a look that’s dynamic, immersive, and digitally native. Rather than using a clean/academic layout, we leaned into a style that mimics the visual language of gaming spaces, from the dark backgrounds and high-contrast elements to the playful accents and energetic composition. We also incorporated images that showcase gamers in action, streaming setups, and gaming hardware like RGB computers and headsets. These design elements aren’t just decorative; they help reinforce the connection between our content and the online spaces where this culture unfolds. The site’s overall tone is meant to speak directly to viewers familiar with Twitch, while still being accessible and engaging to broader audiences.
Meet the Team!
WEB DEVELOPER
Katie Dinh
Katie is a second-year Computer Science major at UCLA, working as the team’s web developer. She was responsible for helping build the website structure and design, as well as integrating relevant data and narratives from teammates in a cohesive manner. She also helped keep the project on track and ensured the group was meeting deadlines.
wEB DEVELOPER / DATA VIZ SPECIALIST
Diego Paz
Diego is a second-year Computer Science major at UCLA who worked on the project as a secondary web developer and data visualization specialist! He was responsible for designing the front page, acting as the team’s historian in gaming, and overseeing the development of representative data visualizations. His favorite game is Minecraft, and his favorite Twitch streamer is Jawsh.
PROJECT EDITOR / CONTENT DEVELOPER
Mia Dowdell
Mia Dowdell is a second-year Psychology major with a minor in Digital Humanities. As the project editor and content developer, she oversaw the collective narrative across the research project by editing both written and visual content to maintain cohesion and clarity. In addition, she worked collaboratively with team members and provided insight on the website’s layout, including assessing typography and color palette, to ensure a clear representation of the research focus to the audience.
PROJECT MANAGER
William Russell
William Russell is a third-year Sociology major and Digital Humanities minor. As project manager, he organized coordination between members of the project, created documents, and helped establish workflow. He brought up the question for this project while also providing the name “Pixel Professors” and found the data set which the project is based around. His favorite video games are GTA and Minecraft; he likes to watch Plaqueboymax on Twitch.
CONTENT DEVELOPER
Yoo Jin Lee
Yoo Jin Lee is a fourth-year Sociology major at UCLA with a strong interest in marketing, content strategy, and data communication. As the team’s Content Developer, Yoo Jin took a role in shaping the project’s narrative arc, ensuring that each section flowed cohesively and effectively communicated the core message. She was responsible for crafting the written content across multiple pages, refining key takeaways, and maintaining a consistent tone throughout the project.
EDITOR / STATISTICAL ANALYST
Jay Enugula
Jay Enugula is a second-year Statistics/Data Science major at UCLA with a minor in data science engineering. He was the team’s editor and statistical analyst for the dataset used. He was responsible for making sure the dataset was clean and useful for data visualization and analysis. His favorite thing about this project idea is how we are able to analyze fan ratings for each streamer and how much influence they have.
ACKNOWLEDGEMENTS
We wish to thank and acknowledge our TA, Julia Stoddard, and our instructor, Dr. Nicholas Sabo, for their exemplary guidance in our investigation of the Twitch ecosystem.