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. It was also found that movies within the genres of action/adventure and romance were very different in the number of lead males, with action/adventure having 111 total males, and romance having only 3.
Past Research and Current Findings
Historically, men and women have been portrayed differently in media. While minimal research has been conducted towards movies, researchers have spent plenty of time looking at
CONTENT ANALYSIS OF GENDER TRENDS 8 media such as advertisements, newspapers, children’s television, literature, and video games.
According to Bandura and Bussey, women are shown as weak and are kept out of powerful roles and situations, while males are more often shown in powerful roles (Bandura & Bussey, 1999).
Women are also more likely to fill a dependent role four times more than males (Eisend, 2009;
Collins, 2011). This research does not correspond to the current research in some aspects, but does in others. Contradicting past research, the current study found that in high ranking movies, there are more females as leads over males as leads. The current study also found that the genre of action/adventure had more male leads then the other genres of comedy, drama, and romance, which supports past research.
Methodological Limitations
Content analysis worked well for the present study, however, more time for the norming process should have been employed. While gathering research, it was easy to get confused about which movies should be included because there were times when multiple genres were listed together (dramatic comedy, romantic comedy, etc). In this study, the first word out of the genre was taken in a case like that, however, the results could have been clearer if movies with multiple genres had been disregarded.
Another limitation to the current study was the method for which the top 100 movies per year were found. The ratings used were calculated by actual movie critics, but the selection of the movies themselves were chosen by normal viewers on flickchart.com. Though the site is controlled, data could have been more accurate if taken from a website in which lists of top movies were created by box office sale numbers or critic ratings.
CONTENT ANALYSIS OF GENDER TRENDS 9
The use of content analysis allowed researchers to both access and acquire a large amount of data in a short amount of time with minimal cost, however, it did not do much in terms of explaining why the findings were or were not significant, it only gave surface information.
Statistical Limitations
If this study is replicated again, researchers should be sure to take into account the number of movies within each genre, in accordance with the number of lead roles. Though there were significant findings found regarding ratings between movies with male lead roles, findings may have been different if the same number of movies within each genre was chosen.
Another limitation to the current study is that ratio should have been measured differently. Instead of using an actual ratio, researchers used the gender of the lead character, which doesn’t accurately depict all of the lead roles. For example, in each movie listing, there were three main characters listed. Rather than taking into account all three characters, only the first one was used. Taking into account each of the characters could have drastically changed the results.
CONTENT ANALYSIS OF GENDER TRENDS 10
References
Aubrey, J. S., & Harrison, K. (2004). The gender-role content of children’s favorite television
programs and its links to their gender-related perceptions. Media Psychology. 6(2), 111-
146. Retrieved from http://cwi.idm.oclc.org/login?url=http://search.ebscohost.com/login.
aspx?direct=true&db=ufh&AN=13247295&site=ehost-live&scope=site
Bandura, A. & Bussey, K. (1999). Social cognitive theory of gender development and
differentiation. Psychological Review. 4, 676. Retrieved from https://lopes.idm.oclc.org/
login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edsgao&AN=edsgcl.6
0273400&site=eds-live&scope=site
Bartsch, R. A., Burnett, T., Diller, T., Rankin-Williams, E. (2000). Gender representation in
television commercials: Updating an update, Sex Roles. 43(9-10), 735-743. Retrieved
from https://blackboard.cwidaho.cc/bbcswebdav/pid-1143500-dt-content-rid-3961079_1
/courses/2017FA-PSYC-250-001/Bartsch%20et%20al_2000.pdf
Collins, R. L., (2011). Content analysis of gender roles in media: where are we now and where
should we go? Sex Roles. 64(3-4):290-298. Retrieved from https://lopes.idm.
oclc.org/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edswss&AN
=000287144600011&site=eds-live&scope=site
Eisend, M. (2009). A meta-analysis of gender roles in advertising. Journal of the Academy of
Marketing Science. 38(4), 418-440. Doi: 10.1007/s11747-009-0181-x.
Ganahl, D. J., Prinsen, T. J., Netzley, S. B. (2003). A content analysis of prime time
commercials: A contextual framework of gender representation. Sex Roles, 49(9-10),
545-551. Retrieved from https://lopes.idm.oclc.org/login?url=http://search.
ebscohost.com/login.aspx?direct=true&db=edswss&AN=00018549500014&site=eds
CONTENT ANALYSIS OF GENDER TRENDS 11
-live&scope=site
CONTENT ANALYSIS OF GENDER TRENDS 12
Table 1
Means and Standard Deviations for Proportion of Males in Genres
Genre Total Mean SD
Action/Adventure 111 2.23 .63
Comedy 83 1.66 .86
Drama 67 1.76 .68
Romance 3 1.33 .58
Note. Action/Adventure differs significantly from Romance genre (p = < .001).
CONTENT ANALYSIS OF GENDER TRENDS 13
7.25 7.2 7.15 7.1 7.05 7
Rating 6.95 6.9 6.85 6.8 6.75 Female Roles Male Roles Gender
Figure 1. There were significantly more female roles with higher ratings (p = .033).
CONTENT ANALYSIS OF GENDER TRENDS 14
Appendix
Appendix A
La La Land
Captain America: Civil War
Rogue One
Deadpool
Manchester By the Sea
The Nice Guys
Doctor Strange
Sing Street
Kubo and the Two Strings
Moana
Hunt for Wilderpeople
Nocturnal Animals
Swiss Army Man
Star Trek Beyond
Finding Dory
Jungle Book
The Edge of Seventeen
Silence
Everybody Wants Some
Fantastic Beasts and Where to Find Them
Captain Fantastic
CONTENT ANALYSIS OF GENDER TRENDS 15
Hail, Caesar
Train to Busan
Fences
Popstar: Never Stop Popping
The Accountant
Magnificent 7
Paterson
X Men: Apocolapyse
20th Century Women
A Monster Calls
Deepwater Horizon
Passengers
Don't Think Twice
13 Hours: The Secret Soliders of Bengazi
Elle
Kung Fu Panda 3
Keanu
Batman vs. Superman
American Honey
Colossal
Sausage Party
Pete's Dragon
War Dogs
CONTENT ANALYSIS OF GENDER TRENDS 16
Jason Bourne
Love and Friendship
Miss Peregrine's Home for Peculiar
Children
Central Intelligence
Ghostbusters
Free Fire
Fundamentals of Caring
Lost City of Z
Suicide Squad
Café Society
BFG
Bad Moms
A Girl With All the Gifts
Warcraft
Neighbors 2
Raw
Godzilla Resurgence
Her
Before Midnight
Inside Llewyn Davis
Gravity
Short Term 12
CONTENT ANALYSIS OF GENDER TRENDS 17
Snowpiercer
Captain Phillips
Nebraska
About Time
Star Trek Into Darkness
Iron Man 3
Only Lovers Left Alive
Pacific Rim
The Way, Way Back
Blue Jasmine
Hunger Games Catching Fire
The Spectacular Now
No Turning Back
Philomena
Hobbit Desolation of Smaug
Lone Survivor
Thor: The Dark World
Secret Life of Walter Mitty
Side Effects
Begin Again
Upstream Color
Ida
The Kings of Summer
CONTENT ANALYSIS OF GENDER TRENDS 18
The Wolverine
The Great Beauty
Batman Dark Knight Returns 2
Oblivion
Fast & Furious 6
Man of Steel
The Great Gatsby
World War Z
Enough Said
Don Jon
Justice League Flashpoint Paradox
Doctor Who Day of the Doctor
Nymphomaniac Volume I
Elysium
In a World…
Warm Bodies
Filth
We're the Millers
August: Osage County
Starred Up
Pain & Gain
Drinking Buddies
Ender's Game
CONTENT ANALYSIS OF GENDER TRENDS 19
The Book Thief
Kick-Ass 2
Anchorman 2 The Legend Continues
Riddick
The Past
2 Guns
Bad Words
Nymphomaniac Volume II
White House Down
Olympus Has Fallen
Whiplash
Guardians of the Galaxy
Interstellar
The Grand Budapest Hotel
Captain America: The Winter Soldier
Birdman
Gone Girl
Boyhood
Edge of Tomorrow
X-Men: Days of Future Past
John Wick
The Lego Movie
What We Do in the Shadows
CONTENT ANALYSIS OF GENDER TRENDS 20
Dawn of the Planet of the Apes
The Raid 2
Big Hero 6
The Imitation Game
Fury
Selma
Calvary
The Guest
Chef
Inherent Vice
22 Jump Street
How to Train Your Dragon 2
The Theory of Everything
Frank
Predestination
Foxcatcher
Love and Mercy
American Sniper
Wild Tales
A Most Violent Year
The Fault in Our Stars
The Drop
Two Days, One Night
CONTENT ANALYSIS OF GENDER TRENDS 21
The One I Love
Force Majeure
Obvious Child
Godzilla
A Girl Walks Home Alone at Night
Wild
The Hobbit: The Battle of the Five Armies
Mommy
Still Alice
The Skeleton Twins
The Equalizer
Paddington
St. Vincent
Neighbors
Pride
Veronica Mars
The Hunger Games: Mockingjay - Part 1
Housebound
Big Eyes
The Boxtrolls
A Most Wanted Man
71
The Judge
CONTENT ANALYSIS OF GENDER TRENDS 22
When Marnie Was There
99 Homes
Top Five
The Amazing Spider-Man 2
They Came Together
The Interview
Phoenix
The Maze Runner
The Book of Life
This Is Where I Leave You
The Voices
Muppets Most Wanted
Lucy
Non-Stop
While We're Young
Dear White People
Noah
Draft Day
A Walk Among the Tombstones
Divergent
Leviathan
Clouds of Sils Maria
The Purge: Anarchy
CONTENT ANALYSIS OF GENDER TRENDS 23
Sin City: A Dame to Kill For
Goodnight Mommy
Maps to the Stars
Madmax: Fury Road
Star Wars: The Force Awakens
The Martian
Room
The Revenant
Sicario
Creed
Kingsman: The Secret Service
Ant-man
Avengers: Age of Ultron
Misson: Impossible - Rogue Nation
Brooklyn
The Lobster
Carol
Dope
Jurassic World
Furious 7
The Man from U.N.C.L.E.
Spectre
Beasts of No Nation
CONTENT ANALYSIS OF GENDER TRENDS 24
Spy
Southpaw
Trainwreck
Tangerine
Everest
45 Years
Mistress America
Cinderella
Chappie
The Hunger Games: Mockingjay - Part 2
Shaun the Sheep Movie
The Final Girls
Turbo Kid
Eye in the Sky
Son of Saul
The Intern
Tomorrowland
Pitch Perfect 2
Krampus
The Visit
American Ultra
The Good Dinosaur
The Age of Adaline
CONTENT ANALYSIS OF GENDER TRENDS 25
Focus
Ted 2
Embrace of the Serpent
Far from the Madding Crowd
Paper Towns
Goosebumps
Magic Mike XXL
The Duff
Sleeping with Other People
Terminator Genisys
Man Up
Demolition
San Andreas
Sisters
CONTENT ANALYSIS OF GENDER TRENDS 26
Appendix B
Signature Assignment Reflection
By the time that we got to the feedback section of PSYC-251, my paper had already been edited by Dr. Fellows, as well as several peers from PSYC-250, so I had very few changes that needed to be made. Feedback from peers in PSYC-251 mainly consisted of punctuation corrections throughout the body of the manuscript, and corrections of what should be italicized in the results section. Another aspect of the drafting and editing process that I utilized was working closely with my group members to compare data, in turn, checking that we were all using the correct data to run our analyses.
If I were to make changes to my manuscript, the first thing that I would do would be to find a better way to list the movie titles that were used for the study. Currently, all titles are simply listed in the appendix, which takes up eleven pages. Although I understand why the titles are listed, I would like them added to the manuscript in a way that is not as intimidating. Another change that I would make is my wording in the Statistical Limitations section. I don’t fully understand the findings as well as I could, and because of that, the wording is not at the level that it could be.
Out of the three learning outcomes, I feel that my biggest strength academic writing and
APA formatting skills. In a recent meeting with Dr. Fellows, she informed me that she was impressed with my work this semester, and felt that I had done well in this area. Personally, I love that APA formatting is so straightforward and that the structure is easy to follow. I look forward to continuing to work on and improve my skills. Application of knowledge of research methods and data analysis is my biggest weakness. Though I can understand methods and analyses in class, it is difficult for me to know how to do them and what they mean on my own.
It was a blessing that peer collaboration was such a big part of class, because if I were to have
CONTENT ANALYSIS OF GENDER TRENDS 27 had to work on my own, I likely would not have done as well as I did. Despite my challenges, I am excited to continue progressing towards a goal of feeling comfortable teaching different methods and analyses to my peers.