Movies and television take on a life of their own in the online world, and few know that better than Amber Cocchiola, ’22, a senior in ֱ State University’s School of Emerging Media and Technology.
After a show or movie is released, dedicated fans flock to the online fanfiction community, , to spin their own stories — making changes, improvements, or just building out the imaginary world. Cocchiola saw this fan-created content as an opportunity to find out what fans want from entertainment media, and what the biggest studios like Disney, Netflix, DreamWorks and Warner Bros. may be missing.
She used skills learned in the course Data in Emerging Media and Technology to collect metadata from the fanfiction website.
“I scraped tags from Archive of Our Own in order to find out what people felt needed fixing across three fandoms,” Cocchiola said. “Using this, I gave a recommendation to show runners in order to create more satisfying endings.”
Her work is now , with step-by-step explanations of her process and the Python code used to accomplish the project. The main findings: Audiences crave emotional relationships with media characters and want less reliance on action and more plots centered on characters and social dynamics.
Cocchiola was one of 16 students who published research online about digital media and society for the Fall 2021 course “Data in Emerging Media and Technology” taught by Assistant Professor David E. Silva, Ph.D. Each student chose what interested them the most about digital media, and their projects investigated a wide range of topics.
Several students, like Visual Communication Design major Alex Baumgarter, ’23, explored data related to gaming. He looked at the .
“I analyzed character pick rates and noted all of the trends that I saw before and after the release of Arcane, which was wildly popular,” Baumgartner said. “Throughout the course I learned a lot about the different methods for collecting data, as well as several careers dealing with data collection and analysis.”
Other gaming topics explored included junior Jacob Berman’s analysis of ; senior Drew Baltzer’s exploration of ; and senior Daniel Hinz’s .
Students also explored:
- How NBA team performance predicts Google search traffic for the team brand ()
- A self-study of their own Instagram use ()
- The Twitter conversations about choosing a new Jeopardy host ()
- Whether digital or traditional artists get more traction on Twitter ()
- How Twitter conversations can influence the Emmy Awards ()
Students used a variety of technical skills to complete their research including coding in Python, writing and publishing online using Jupyter Notebooks, wrangling data using the pandas library for Python, visualizing data using matplotlib, and conducting simple statistical analyses. These skills not only help build new knowledge about digital media, but position students to succeed in a data-centric and digital, technical economy.
“This class expanded my Python skills so I could scrape the page, organize the data, run stats tests, and collect the findings in one comprehensive document through a structured and iterative process,” Cocchiola said.