The need for personalized summaries of media content has been driven by the recent and anticipated explosive growth in the media world. In this paper we present a methodology and a supporting user study for generating user profiles and content features that can be used to automatically create personalized summaries of broadcast television content. We determined a mapping, from users' personality traits measured by commonly available personality tests, to computable video features that such personality traits appear to prefer. Three common personality profiles (Myers-Briggs, Merrill Reed, and Brain. exe) were elicited from 59 subjects, together with their preferred summary of news, music, and talk show videos. A factor analysis between the personality traits and the features in preferred summaries indicated that only some traits (e. g., gender, extraversion, control orientation, intuitiveness, etc.) and only some features (e. g., faces, reportage, text, chorus, host, etc.) had predictive value. The mapping of personality to feature also differed by genre. However, in general, extraverted users tended to prefer directly experienced content, while introverted users preferred content mediated through analysis. A validation user study is in progress.