Marc Choueiti's research while affiliated with University of Southern California and other places
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Publications (5)
In this paper, we introduce the Moral Narrative Analyzer for Movies (MoNA-M), a web-based, hybrid content-analytical platform that combines automated and human content codings to extract moral content from popular film scripts. We present a computational pipeline that parses film scripts in both PDF, as well as text format, and subsequently extract...
Each year, USC Annenberg’s Media, Diversity, & Social Change Initiative produces a report examining gender and race/ethnicity on screen and behind the camera across the 100 top‐grossing fictional films. A total of 700 films and 30,835 characters have been analyzed across the 100 top‐grossing films of 2007, 2008, 2009, 2010, 2012, 2013, and 2014 (ex...
The purpose of this content analysis was to examine gender-related portrayals in popular G-rated films. Our research questions
addressed the prevalence and nature of males and females in general-audience fare. To answer our research queries, 101 of
the top-grossing box office films released theatrically in the United States and Canada from 1990 to...
Citations
... In fact, the opportunity for Japanese people to see real or screen versions of Caucasian faces is greater than the opportunity for Norwegians to see Japanese faces. Smith et al. (2015) reported that in the Hollywood 100 top films of 2014, 73.1% of the main characters of movies were Caucasian, while Asian actors accounted for only 5.9%. Therefore, ordinary Norwegians are seldom exposed to East Asian people or electronic versions of their faces. ...
Reference: The other-race effect in the uncanny valley
![[object Object]](https://i1.rgstatic.net/ii/profile.image/669149684572177-1536549125416_Q64/Traci-Gillig.jpg)
... Although, she also argues that a sexist environment may be driving the non-generic interpretation of generic masculine pronouns. Further studies have corroborated that people = male, showing repeatedly that when masculine pronouns are used generically, people think of males specifically [21,23,25,50]. However some, Hamilton [23] for example, have shown that people continue to think of males more than females even when neutral and inclusive language are used in stimuli. ...
... Differences in volume and language were found to be influenced both by the gender of the writers themselves, and that of the characters being written. For example, a study found that films written by females include nearly 15% more female characters on average than films written by males (Smith & Choueiti, 2011). Schofield and Mehr's (2016) found that male and female characters are written to use different language patterns than male characters. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/446294444515330-1483416295208_Q64/Laurel-Felt.jpg)
