This project was the result of condensing the front section of the New York Times into one page. I collected information from the newspaper manually and attempted to interpret the data to create something more meaningful.
Newspaper: New York Times
Date: Sunday, October 25th 2015
Personal role: data collection, data interpretation, data visualization
- How do you display information in a way that says something about the data?
- How can you make it accessible to anyone?
An infographic that takes data about the New York Times and converts it into a scannable format
Data collection consisted of approaching the data in many different ways, trying to find a story within the data. While infographics allow people to quickly understand information, they're useless without having a point behind them.
The one thing that really stood out to me was that the majority of stories on the front page concerned death, so I decided to focus on that. I collected as much information as I could related to death from the front section, in order to give me a good amount of information to curate.
Data was collected in the following way:
Collection of any interesting data
The first collection was to collect any information we thought was interesting as we read through the section. This varied in terms of types of data—some of it was quantitative (number of words in different articles, number of obituaries, size and number of advertisements) while some of it was qualitative (themes of the articles, emotional language, evidence of bias).
Narrowing of Topic
Once the first pass was done, we analyzed what information we had and drew links between these ideas. One thing that stood out to us was the idea of death that was very prevalent throughout a lot of our data collection.
Further Data Collection
Once we had a topic, we went back over the section and started collecting more information relevant to death. We tallied (by hand) more details (e.g. number of people dead, number of advertisements adjacent to articles about death). These details were related to qualitative data, but we attempted to find ways to quantify them as quantitative data is easier to present in visual form. We also found PDF versions of the articles (or used OCR for certain pages) to analyze the text, such as finding character counts for the obituaries.
Certain details were still intriguing to us, but the newspaper itself lacked the information we wanted to know. We then researched those tangents online, such as finding out the price of a printed obituary.
The final infographic is the size of a single page of a New York Times broadsheet, which allows it to be slipped inside.
One problem that I came across was that to make sure that the information wasn't being visually deceptive, I had to calculate areas for the triangles in the diagrams, rather than just using measurements. Otherwise, due to the nature of triangles, doubling the height of the triangle would more than double the area which would make that data look much larger than what it actually is.
Original bad scaling of triangles
Final scaling of triangles
My parents are journalists, which has led me to have a heightened awareness of ethics surrounding information, especially in the media. While I do believe that infographics are very useful and can empower people, this project raised ethical questions related to data visualization:
What information is important enough to be represented?
The opposite to this question is also important: what information do we consider unnecessary? Creating data visualizations is acting as the gatekeeper of information—providing limited information is ideal because it helps users make sense of the data, but too little information can bias their interpretations of that data.
What information should be emphasized?
This is most relevant to visual design. Once data is determined to be important enough to be portrayed, the visual hierarchy will also imply certain information is more important than others.
Is being objective necessary?
The audience and aim of the infographic can mean that being biased is not necessarily a bad thing (e.g. in advertising, politics). However, what stops this from bridging into being propoganda and/or false news?