Introduction -- Why we need film and series suggestions -- How algorithmic recommender systems work -- Cracking the code, part I : developing Netflix's recommendation algorithms -- Cracking the code, part II : unpacking Netflix's myth of big data -- How real people choose films and series -- Afterword : robot critics vs. human experts -- Appendix : designing the empirical audience study.
Focusing on curation-style video on demand services, this book examines MUBI, a leading independent platform that emphasizes human-generated recommendations over algorithms. It explores how MUBI addresses concerns about digital content consumption, promoting quality and discovery amidst a cultural surplus. Utilizing a comprehensive methodology, including interviews and audience studies, the analysis sheds light on MUBI's role in content aggregation and community building. The work serves as a case study for understanding the impact of major tech companies on art cinema and media diversity.
The book offers a comprehensive analysis of the evolution of German historical films since the fall of the Berlin Wall, highlighting their critical acclaim and box office success. It explores the emergence of the New German Cinema, characterized by its radical style, content, and political engagement. By examining major trends and films, the text challenges conventional narratives and delves into how contemporary cinema interacts with different historiographical approaches and its own history, reflecting a complex post-wall cultural landscape.