Many of our great cultural lessons come to us from stories. Fables and fairy tales, nursery rhymes and novels all weave a tapestry of truisms that we transmit through generations. Traditional forms of storytelling are recycled and renewed by writers and artists across media and over time. Today, our cultural myths are not only preserved in archives and memory but through cinematic adventures on grand scales. In popular films, story conflict may transcend the simple matter of good vs. evil to communicate more complex virtues to viewers. To address the intricacy of analyzing these lessons, researchers have distilled them to more foundational altruistic moral intuitions and egoistic moral motivations. In a previously project funded by the JTF we delivered an online platform (The Moral Narrative Analyzer, MoNA) which integrated text-mining of film scripts and narrative analysis alongside input from specially-trained human coders in order to identify moral intuitions, moral motivations, and moral conflict in popular movies. In the proposed Phase-II of this project we expand our focus to include a broader range of films, advance our analytical procedures, and include the performance modeling of popular movies based on their virtuous content. The project includes three tiers. Tier one includes a large scale content analysis and advanced movie performance modeling. Tier two integrates the comprehensive analyses of film character data and film reviews collected by the Inclusion Initiative at USC’s Annenberg School for Communication. A final third tier integrates the extraction of moral information in textual, pre-production movie scripts with computationally-extracted, audio-visual features and subtitles of real-world, post-production motion pictures to assess the prevalence of moral information and their predictive accuracy for movie performance.
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