Genre-typical narrative arcs in films are less appealing to lay audiences and professional film critics

Abstract

People tend to like stimuli-ranging from human faces to text-that are prototypical, and thus easily processed. However, recent research has suggested that less typical stimuli may be preferred in creative contexts, such as fine art or music lyrics. In an archival sample of movie scripts, we tested whether genre-typicality predicted film ratings as a function of rater role (novice audience member or expert film critic). Genre-typicality was operationalized as the profile correlations between linguistic arcs (across five segments, or acts) for each script and within-genre averages. We predicted (1) that critics would prefer more disfluent (genreatypical) films and general audiences would prefer fluent (genre-typical) films, and (2) that these differences would be most pronounced for genres expected to be more entertaining (e.g., action/adventure) than challenging (e.g., tragedy). Partly consistent with our hypotheses, the results showed that critics gave higher ratings to action/adventure films with less typical positive emotion arcs. However, regardless of audience-member or professional-critic status, higher ratings were attributed to films that were more genre-atypical (or disfluent), in terms of analytic thinking, narrative action, and emotional tone, across all genres except family/kids films. Such findings support the growing literature on the appeal of disfluency in the arts and have relevance for researchers in psychology and computer science who are interested in computational linguistic approaches to attitudes, film, and literature.

Better abstract or concrete, narrating or not: optimal strategies for the communication of innovation

“…Van Laer et al, 2019a). While the innovation literature has previously examined the role of storytelling in communicating the innovation process, with a particular focus on the comparison between "ongoing journeys" and "results-in-progress" (Manning and Bejarano, 2017;Cappa et al, 2021), our research extends this body of work by measuring the degree of narrativity used to communicate innovation and demonstrating that stories fitting with the narrative arc (early staging, increasing plot progression, reverse-U shaped cognitive tension; Nalabandian and Ireland, 2019;Boyd et al, 2020) significantly enhances audience engagement. Moreover, we establish that this effect is contingent upon emotional tone, revealing instances where storytelling can be more effective or fail to engage.…”

“…One promising approach is based on the narrative arc analysis, which aims to identify and quantify the common structure that underlies narratives (e.g. Nalabandian and Ireland, 2019; Boyd et al ., 2020). By connecting characteristics of language with the theory of narrativity, Boyd et al .…”

Linguistic gender congruity differentially correlates with film and novel ratings by critics and audiences

“…Genre often assists audiences and readers when choosing what films to watch or what books to read, and audience and reader ratings may be influenced by whether specific language within the narrative is consistent with its genre. Past research [ 37 ] illustrates that both lay audiences and professional critics are more likely to highly rate films with genre-typical language. Thus, if certain gender-linked language categories used in the present analyses are typical of one genre or another, that may skew the results.…”

“…The current sample of film scripts was based on a sample from a previous study examining genre-typical language in film [ 37 ] and was obtained from the drama category of the Internet Movie Script Database ( n = 509; IMSDb; https://www.imsdb.com ). However, in order to acquire at least 50 film scripts written by women, we gathered additional scripts ( n = 5; Young Adult ; Lady Bird ; Middle of Nowhere ; Somewhere ; The Invisible Woman ) that were not available on IMSDb from alternative script repositories (Indie Film Hustle and Hollywomen).…”

Market Segmentation in the Film Industry Based on Genre Preference: The Case of Millennials

“…For example, El Bolock et al (2020) proposed a film meta recommender algorithm, which starts by getting the genre of films the user prefers before applying machine learning techniques. Nalabandian and Ireland (2019) provide an extensive literature review on how genre preference affects consumer behaviour. Therefore, the film genre can have a detrimental impact on how the film is going to be accepted by the audience and how and to whom it will be recommended.…”