  We consider the noir classification problem by exploring noir attributes and
what films are likely to be regarded as noirish from the perspective of a wide
Internet audience. We use a dataset consisting of more than 30,000 films with
relevant tags added by users of MovieLens, a web-based recommendation system.
Based on this data, we develop a statistical model to identify films with noir
characteristics using these free-form tags. After retrieving information for
describing films from tags, we implement a one-class nearest neighbors
algorithm to recognize noirish films by learning from IMDb-labeled noirs. Our
analysis evidences film noirs' close relationship with German Expressionism,
French Poetic Realism, British thrillers, and American pre-code crime pictures,
revealing the similarities and differences between neo noirs after 1960 and
noirs in the classic period.
