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Content Analysis of Gender Trends 1 Running head: CONTENT ANALYSIS OF GENDER TRENDS 1 A Comparative Content Analysis of Gender Trends in Current Films Sydney Butler, Patricia Feasel, Sharon Haylett, and Thomas Parker The College of Western Idaho CONTENT ANALYSIS OF GENDER TRENDS 2 Abstract For many years, gender has been misrepresented in media. Men are shown in dominant roles while women are shown in dependent roles. Data was collected from films from the years 2013, 2014, 2015, and 2016 using content analysis to determine if there was any difference between male and female lead characters depending on genre or rating of each film. Although content analysis gave easy to understand, replicable data, it was not helpful in understanding why there was a significant difference in rating of movies with female lead roles, and why the action/adventure genre differed significantly from the romance genre in number of male starring characters. Keywords: gender, media, movies, male, female, content analysis CONTENT ANALYSIS OF GENDER TRENDS 3 A Comparative Content Analysis of Gender Trends in Current Films Are men and women represented differently in current media? Extensive research has taken place by studying various types of media such as advertisements, literature, and video games, but an inadequate amount of research has been applied towards movies. According to previous research, males outnumbered females 2:1 in children’s T.V. (Aubrey, & Harrison, 2004), and males appeared two to three times more often than females in newspaper coverage and local television news coverage (Collins, 2011). Women are shown as weak in media, while men are shown as powerful, driving societal perceptions of keeping women out of powerful situations and roles (Bandura & Bussey, 1999). Women are less likely to be portrayed with professional roles or using non-domestic products (Bartsch, Burnett, Diller, & Rankin-Williams, 2000: Ganahl, Prinsen, & Netzley, 2003), while men are shown as managers and women as clerical in workplace situations on television (Bandura & Bussey, 1999). Women are more likely to fill a dependent role four times more than males (Eisend, 2009; Collins, 2011). Within society, media misrepresents gender through character roles which could impact individuals negatively in both their personal and professional lives, by maintaining archaic schemata. Men are more likely to be casted into a main character role depending on movie genre. This investigation set out to demonstrate how genders are unequally depicted across the top 100 movies in the last four years, and looked at the gender bias in lead roles across genres of movies from 2013, 2014, 2015, and 2016 from the website flickchart.com. For the purpose of this study, focus was on the first genre listed for each movie, and included those listed within the genres of action/adventure, comedy, drama, and romance. The genres were focused on because they gave a CONTENT ANALYSIS OF GENDER TRENDS 4 good representation of the full coverage of movie genres. Listings were allocated based on film popularity and popular rankings from users on the site. These misrepresentations of gender in media beckons our purpose for this study: to determine if men and women are represented differently in current movies across the genres of action/adventure, drama, comedy, and romance. This study employed the method of content analysis and w to answer the following questions: (Q1) Does the lead being male or female impact the rating of the film? (H1) Movies with male leads will have higher ratings then movies with female leads. (Q2) Is there a higher male to female ratio in genres of action/adventure, drama, comedy, and romance? (H2) If the movie is action/adventure, drama, comedy, or romance, then there is a higher ratio of male-female then female-male. (Q3) Is there a relationship between the male to female ratio and ratings from Rotten Tomato? (H3) If the movie has a higher rating from Rotten Tomatoes, then there will be a higher male to female ratio. Content analysis is the study of written communication, and movies are exactly that, which is why it was chosen as the methodology. Due to the fact that content analysis was the method utilized, there was a very low cost associated with the research project, there was no contact with people required, and the study is easily repeatable. Cons to the method however, are that the data is purely descriptive and the problem can be seen, but not understood. Method Participants The corpus contained the top 100 movies from 2013, 2014, 2015, and 2016, as classified by Flickchart.com, was scrutinized, and 400 total films were narrowed down to 265 total films by only picking films that were categorized in the genres of action/adventure, comedy, drama, and romance. Any films outside of these genres were disregarded. All films were retrieved from CONTENT ANALYSIS OF GENDER TRENDS 5 public domain, Flickchart.com, and ratings were retrieved from public domain, rottentomatoes.com Measures Data collection was completed by year, with each year being done by an individual researcher. The following codes were created: The first code indicated which movie was being coded within the years 2013-2016 in the top 100 movies listed on Flickchart.com. It was a non- qualitative variable that included the name of the movie being coded (See Appendix A). The second code indicated the gender of the first starring character listed on the website Flickchart.com on the movie listing per year. The third code indicated the first genre listed if it met predetermined genres of action/adventure, comedy, drama, and romance from Flickchart.com. The fourth code indicated the number of starring characters that were male, out of the three characters that were listed on Flickchart.com. The fifth code indicated the number of starring characters that were female, out of the three characters that were listed on Flickchart.com. The sixth code reflected the average critic rating (Tomatometer) on a 10-point scale from rottentomatoes.com. Procedure Data was collected for male and female lead roles across movie genres from 2013-2016, using entries from the website Flickchart.com. Lead roles were determined by taking the first listed starring character of each movie. Corresponding ratings were taken from the website Rotten Tomatoes, in which ratings from the site are measured by the reviews and feedback of hundreds of film and television critics using a 10-point scale. Data entries and results were kept on a password protected computer. CONTENT ANALYSIS OF GENDER TRENDS 6 To determine whether males and females differed in representation in current media, all researchers first agreed on which variables would be studied. After discussion, researchers decided that the top 100 films from the domain Flickchart.com would be analyzed using the variables lead, genre, male, female, and rating, to see if males and females were represented differently between genres, and if films with male leads attained higher ratings than films with female leads. The top 100 movies per year were taken from Flickchart.com, because the films were ranked by average viewers, so rank was solely determined by how much viewers enjoyed the film. From there, researchers went through a norming process, from the top 100 movies from 2012, to confirm that all data would be collected in the same manner. Each researcher looked at the data, chose appropriate movies based on genre, listed the gender of the first recorded starring character, entered the proper code for genre, recorded the total number of both males and females, and noted the genre for each film. Rating was taken from rottentomatoes.com, and the rating recorded was the critic rating (Tomatometer). Following the norming process, researchers completed data collection on selected years, following all rules from the norming process. Data regarding movie title, genre, and lead character gender was found from Flickchart.com, while rating was found from rottentomatoes.com. All data was combined into an Excel spreadsheet on a password protected computer. No human subjects were recruited for this study. Results It was hypothesized that movies with male leads would have higher ratings than movies with female leads. To test if there is difference in rating between movies with male lead roles (M = 6.91, SD = 1.00) and female lead roles (M = 7.19, SD = 0.97), an independent samples t-test CONTENT ANALYSIS OF GENDER TRENDS 7 was used. The independent samples t-test revealed that there was a significant difference in rating of movies with female lead roles, t(262) = -2.15, p = .033, d = 0.28. Movies with female lead roles had higher ratings than those with male lead roles (see Figure 1) It was hypothesized that action/adventure, comedy, drama, and romance movies would have a higher ration of male-female leads. A one-way ANOVA was conducted to detect difference in number of male starring characters between action/adventure, comedy, drama, and romance genres. There was only one significant effect, F(3, 260) = 12.28, p < .001, η2 = 0.12. Post hoc comparisons using the Tukey HSD test (p < .05) showed that the action/adventure genre (M = 2.23, SD = 0.63) was significantly different than the romance genre (M = 1.33, SD = 0.58). Number of males across action and romance genres was significantly different. For additional descriptive statistics, see Table 1. It was hypothesized that movies with higher ratings would have a higher male-female ratio. To test if there was a relationship between number of male stars in movies and their ratings, a Pearson correlation was conducted. The test showed no significant findings, r(262) = .00, p = .989. Discussion After completion of the current study, it was found that movies with female leads held higher ratings than movies with male leads.
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