Welcome to my exploration of audiovisual content recommendation algorithms! This project is a blend of my passions: technology, data analysis, and social sciences. It's not just about coding; it's about understanding the digital landscape and how it influences our choices and cultural perspectives.
In this project, I dive into various content recommendation algorithms for audiovisual media, using Python for its flexibility and analytical depth. My goal was to dissect and compare these algorithms, uncovering their unique impacts on user recommendations and cultural consumption. This endeavor went beyond technical analysis, as it aimed to inform future public policies in Europe concerning streaming platform consumption.
Navigating these algorithms' complexities, I focused on consistently differentiating their recommendation patterns. The primary challenge was integrating real-world datasets to enhance the project's applicability and my learning experience. This project was a crucial part of my academic journey at Carlos III University of Madrid, contributing to the broader "Diversity and Audiovisual Services on Subscription Demand" project.
If I were to rebuild this project, I'd integrate real-world datasets from the outset, possibly leveraging resources like JustWatch’s extensive catalog. This approach would offer more practical challenges and insightful results, enhancing the project's relevance in the ever-evolving world of media consumption.
This project is just the beginning. My journey continues as I further explore the intersection of technology and social impact in the world of digital media. Stay connected to see where this adventure takes me next!