Machine Learning Approaches to Content Recommendation: Enhancing User Experience on Netflix
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Abstract
In an era characterized by the proliferation of digital media consumption, understanding the intricacies of narrative construction and viewer engagement in streaming platforms has become paramount. This paper presents a multifaceted approach to analyzing and interpreting the dynamics of narrative complexity in Netflix originals. Leveraging computational linguistics, semantic analysis, and machine learning methodologies, we delve into the semantic substrate of streaming media, unraveling the underlying narrative structures that govern viewer perception and reception. Our research employs a hybrid framework that integrates textual analysis with visual semantics, allowing for a holistic examination of cinematic content. Through the extraction of linguistic features, sentiment analysis, and entity recognition techniques, we uncover latent patterns within the textual corpus of Netflix descriptions and synopses. Concurrently, employing computer vision algorithms, we decode the visual motifs and symbolic representations embedded within the visual content of Netflix productions. Furthermore, our study delves into the temporal evolution of narrative complexity, tracing the trajectory of storytelling paradigms across different genres and time periods. By applying network analysis to cultural production data, we unveil emergent narrative structures and identify key influencers shaping the evolution of digital storytelling. Ultimately, our research contributes to the burgeoning field of digital humanities by providing a comprehensive framework for analyzing and understanding the intricate interplay between textual and visual elements in streaming media. By elucidating the mechanisms driving viewer engagement and narrative immersion, our findings offer valuable insights for content creators, platform developers, and scholars alike, paving the way for enhanced viewer experiences and informed content curation strategies in the digital landscape.