Data is data is data
It has long been the contention of the Interhacktives that good data work is good data work, regardless of the subject. While there is prestige associated with using a data visualisation to illustrate a point about obesity across Europe or in election coverage, it is all too easy to forget that good data visualisations can be used to illustrate anything for which there is data.
For instance, here is a quick visualisation thrown together comparing the most commonly used words from the script of The Best of Both Words Part I, the Star Trek: The Next Generation season 3 final, with the same from Part II, the season 4 opener.
Frivolous? Perhaps. But to a Trek enthusiast, that wordcloud can prove a point about Geordi’s near invisibility during season 4, and handily it proves my point too; data can be used to illustrate our favourite pieces of pop-culture.
Here, then are some of our favourite pop-culture data visualisations from the past year. Over the coming week we’ll be featuring interviews with some of the people who made them, with a focus on how they feel data can be used to make us reconsider our favourite films, music and shows.
Scatterplot of the Most Overrated Films
Made by student Benjamin Moore, using the rCharts opensource tool, this great chart shows the correlation (and sometimes startling lack thereof) between film critics and audiences’ opinion of the same film. Made using data gleaned from the Rotten Tomatoes API, it finally offers proof that critics were wrong about Step Up being a mediocre movie, and About a Boy being a good one.
In this write-up of his process, Benjamin notes that the Rotten Tomatoes API is permissive in the number of calls it allows but restricting in the data it actually offers up. He also notes that his method for gathering the data was likely by its nature to underperform, since by searching using the ‘similar films’ term was likely to pull in several films from the same serious, which would likewise redirect to the other. Nevertheless, a fantastic piece of data work that shows us how sharply divided audience and critical consensus can often be.
Rappers’ Vocabularies, Ranked
Designer and data scientist Matt Daniels is keenly aware of the ability of data to change how we look at pop culture. In this analysis, he ranks various rappers based on the diversity of their vocabulary in their first 35,000 lyrics. By his metrics, he shows that many are in fact more lyrically ambitious than Shakespeare was in the first 5,000 words of seven of his plays. A few even rank above Herman Melville’s notoriously verbose Moby Dick.
While there are issues with this method of analysis, some noted in this io9 article by which it came to widespread public attention and others noted in his initial write-up, it’s still a great piece of data work. Matt is no stranger to using data to analyse pop-culture: His [possibly not safe for work] “absurdly nerdy look at how hip-hop invented the most important slang of our time” and data-driven look at Outkast both show how data work can direct attention towards topics that might not otherwise have received it.
Graph TV
Finally, a means to pinpoint the exact moment your favourite television programme took a dip in quality. Created by software engineer and super-fast Rubik’s Cube solver Kevin Wu, this fun data visualisation allows you to  see individual IMDB scores for television programmes, and an aggregated line for each season which shows how critical consensus changed as the season progressed.
Visualisation of Narrative Structure
Good data visualisations can even help us shed new light on old, paper-bound stories. This interactive visualisation, created by neuroscience Ph.D students Natalia Bilenko and Asako Miyakawa, details the character interactions by chapter in books such as Kafka On The Shore and The Hobbit. They also show a sentence by sentence breakdown of how many sentences in each have a positive or negative connotation and, as Natalia’s expertise is in the mind’s response to linguistic ambiguity, she should know how these effect the reader.
Did we miss any great, pop-culture driven data stories? Let us know in the comments below!
Chris M Sutcliffe is a trainee journalist at City University London, specialising in data and online journalism. He's also a webcomic artist and writer, but we try not to talk about that.