Data Visualizing Westworld

This should be really fun for fans of the popular HBO series, Westworld, especially if you’re also a bit of a data wrangler.  Folks at Mode gather theories about characters and plot, turn them into data visualizations and display them at WESTWORLD IN DATA.  They also extract data from the shows themselves with findings, for instance, on which characters/genders speak the most.

westworld-robot-in-progress-1024x576

Read more about the this project here, where they invite us to tune in weekly:

“We’ll be updating Westworld in Data with data from the most recent episode every Monday evening, so be sure to bookmark the site and check back. We’ll also be doing more Westworld analyses as the season progresses. Sign up for our weekly newsletter to keep up with our data adventures.”

Echoes of Cultural Indicators at the Geena Davis Institute on Gender and the Media

screentimeThese days George Gerbner must be smiling down in the direction of  Mount Saint Mary’s University, home of the Geena Davis Institute on Gender and the Media which, since 2008, has built up a lot of research on gender prevalence in family entertainment.  To boost their mission of tracking gender and minority inequality on the screen (with financial assistance from Google.org) they are turning to cutting edge software, the Geena Davis Inclusion Quotient (or GD-IQ), comprised of video- and audio-recognition technology matched with algorithms “to identify gender, speaking time and additional details about characters presented in films, television shows and other media.” Automating this kind of data collection really changes the playing field from back in the day, i.e. the 1970s and 1980s when this sort of pioneering media research relied on video tape and manual coding.

Long before anyone was thinking about casting inequities, before celebrities were making speeches about such at award ceremonies, Gerbner was documenting the disconnect between populations inside and outside of the television set.  He noticed, and then systematically tracked, how the race, age, and gender of characters did not match the reality in the “real” world. To study this dynamic, he built an ongoing landmark research project called Cultural Indicators (1972-1996), amassing a cumulative database describing many thousands of characters and programs by key features, many of them demographic.

Check out a good summary of a 10-year study of TV demographics (based on the analysis of 19,642 speaking parts appearing in 1,371 major network prime time and Saturday morning children’s programs) as revealed by the Cultural Indicators Project in this 1982 piece written for American Demographics, The World According to Television” (Gerbner, Signorelli, October, 1982). 

Over 10 years later Gerbner observed, in a chapter called “Casting and Fate: Women and Minorities on Television Drama, Game Shows, and News” that appeared in Communication, Culture, Community (edited by Ed Hollander, Paul Rutten and Coen van der Linden, 1995):  subpage

“A general demographic overview finds that women comprise one-third or less of characters in all samples except daytime serials where they are 45 percent and in game shows where they are 55 percent. The smallest percentage of women is in the news (28%) and in children’s programs (23%). Even that shrinks to 18 percent as the importance of the role rises to ‘major character’.

While all seniors are greatly underrepresented, visibly old people, roughly 65 and above, are hardest to find on television. Their representation ranges from none on the youth-oriented Fox network and about 1% on network daytime series to less than 3 percent in the other samples. In real life, their proportion is 12% and growing. African-Americans are most visible on Fox and in game shows. On major network prime-time programs they are 11% and on daytime serials 9% of all characters. They are least visible on Saturday morning children’s programs. (Many cartoon characters cannot be reliably coded for race.)

Latino/Hispanic characters are rarely seen. Only in game shows do they rise significantly above 1 percent representation. Americans of Asian/Pacific origin and Native Americans (‘Indians’) are even more conspicuous by their absence. Less then 1 percent (in the case of Native Americans 0.3 percent) is their general representation.

Almost as invisible are members of the ‘lower class’ (judged by a three-way classification of the socio-economic status of major characters). Although the U.S. census classifies more than 14 percent of the general population, 29 percent of Latino/Hispanics, and 33 percent of African Americans as ‘poor,’ and many more as low-income wage-earners, on network television they make up only 1.3 percent of characters in prime time, 1.2 percent in daytime, half that (0.6 percent) in children’s programs, and 0.2 percent in the news.” p.126-127

Fast forward to the Geena Davis Institute and the GD-IQ, and we have, as reported in The New York Times, How Long Is an Actress Onscreen? A New Tool Finds the Answer Faster (Melena Ryzik, Sept. 14, 2016), Dr. Shri Narayanan, an engineering professor at the University of Southern California, studying the 200 top-grossing, non-animated films of 2014 and 2015 to find that “overall, in 2015, male characters were both seen and heard about twice as much as female characters. Parity on paper does not help: In films with male and female leads, the men nonetheless appear and speak more often than the women. Even in films with female leads, the men still get nearly equal screen and speaking time.”  

This new, emboldened-by-technology research is asking the very same questions Gerbner and his team of researchers here at the Annenberg School first posed so many decades ago.  There is even talk, once the software gets more fine-tuned, to look at STEM fields—how characters who play scientists and engineers are cast in screen roles,  how much speaking do they get to do, etc.  Sound familiar?  See Scientists on the TV Screen (Gerbner, Gross, Morgan, Signorelli) in Society May/June 1981).

Let’s hope today’s research on screen diversity can be the change-agent in the 21st century that George Gerbner hoped his would be in the previous one.