Likability-Based Genres: Analysis and Evaluation of the Netflix Dataset
Andrew McGregor Olney · eScholarship (California Digital Library) · 2010
This paper describes a new approach to defining genre.A model is presented that defines genre based on likability ratings rather than features of the content itself.By collecting hundreds of thousands of likability ratings, and incorporating these into a topic model, one can create genre categories that are interesting and intuitively plausible.Moreover, we give evidence that likability-based features can be used to predict human annotated genre labels more successfully than contentbased features for the same data.Implications for outstanding questions in genre theory are discussed.