NYC Emotional Census
Introduction
NYC Emotional Census is the result of my thesis research work. My thesis is about sharing personal data and stories to empathize with others and create emotional connections.
How can I achieve this idea, in a diverse and populated place like NYC?
To respond to this question, I need to explain that I believe that no matter how much NYC residents know and are part of the city’s diversity, it is necessary to be exposed to others’ emotional stories to connect with people. I want to clarify that I am aware that every individual experiences and process emotion and situations differently than others, but it is the action of sharing, and realizing that we experience similar emotions, where we can empathize and connect with others.
To prove my theory, I need to demonstrate that we could develop empathy and connect with others by learning and understanding our similar emotions. Therefore, I start by asking what are the most common things that could happen to a New Yorker? And what emotions do we experience in NYC?
Based on the 2020 NYC census, every neighborhood in the city has its characteristics. They differ economically, demographically, culturally, and urbanistically, but with The NYC Emotional Census, I found that certain emotions that residents experience are similar regardless of their neighborhood.
Process
After various interviews, I created a survey to collect data about common issues and emotions that NYC residents experience. Each question of the survey has a multi-choice answer.
For the purpose of this work, I used the data from the first 19 respondents. My intention with this information is to create connections and avoid comparisons.
The first sketch was a map showing pins and colored arrows that connect one person to another. The arrows had different colors, based on the topic. I didn’t move forward with this idea because it highlighted the individual and not the connections through the emotions.
After various user testing, I realized that the visualization had to be broken down into various parts to ensure a clear message. To tell the story, my visualization is divided into three sections.
Section I consists of a map of NYC. This is the introduction to the project. It locates the audience in a specific place, and it says that what comes next is about people who live in NYC. There are colored pins, a color per borough. The pins show the location of the 19 respondents in their respective neighborhoods. When the audience clicks on one pin, a tooltip pops up with a short description of the respondent. The tooltip shows information that is not presented in the final diagram.
Section II consists of the visualization of the responses to the survey using pie charts. My intention is to showcase the different responses in percentage. Therefore, the audience will be able to identify the quantitative aspect of the information.
Section III the final visualization shows how people from the different boroughs connect through similar emotions or situations that occur while living in NYC. I selected eleven data points that represent emotions and situations. For this section, I considered using a chord diagram since it is ideal for visualizing similarities within a data set or between different groups of data, but I realized that it was going to look very crowded. I also considered the non-ribbon chord diagram which emphasizes the connections within the data. To create my diagram I used the characteristics of a chord diagram and a non-ribbon chord.
Eleven black nodes represent the data points. The data points are centered in the diagram. Selecting a data point will highlight the connections to the NYC residents. The residents are grouped in colored nodes according to their neighborhood. Residents can be filtered by gender, helping to find more specific connections. To avoid a cluttered chart, I locate the resident nodes above and under the eleven data sets.
Use of color
The challenge I had on this part of my project was the amount of information that had to be classified by color: emotions and neighborhoods. In my first sketch, I used a color per neighborhood so that I could use the same colors throughout the different charts and pins on the map, but it looked crowded.
I resolved this problem by grouping the neighborhoods by boroughs. Each borough has a color and the neighborhoods have a monochromatic variation.
To represent the emotions in the pie chart, I use a variation between warm and cold colors. The colors go from light to dark depending on the emotion. For example, to visualize the chart about people that experienced depression, I used dark blue for those who responded yes, and light pink for those that responded no. Those that responded “I don’t know” were colored with light purple, to create a middle ground between the pink and the dark blue. The next chart, about who contacts emotional support, showed that the majority of respondents didn’t look for emotional support. In this case, I switched the colors, the section of the pie that represents “No contact” is colored in dark blue, and the one that represents “Yes’’ is colored in pink. I did this because in this case, not contacting emotional support could represent that the respondents can’t afford it, or couldn’t find it, or they don’t need it. Throughout the emotional part of the survey, the dark blue represents conflicting emotions.
For the housing part of the survey, I played between a lighter and darker version of pink. The darker one represents the answers of those who experienced conflict related to their houses.
Use of technology
I use D3.js to visualize the pie charts. I found the reference code from Observable, Inc. It was my first time using D3.js, so it took me a while to figure out how to connect the reference code to my own project. D3.js returned an SVG object that had to be appended to the HTML body, which took trial and error.
Final thoughts
During the design process of this project, I re-think the survey questions, as well as what should I display? The majority of the questions are very personal and sensitive. Since my intention is not to expose people, the survey is completely anonymous.
An anonymous survey, allows the audience to focus on the connection through experiences and emotions. How many people felt isolated, how many people struggled to find friends, or where do they live? This leaves a bigger question, why isolation, depression, and loneliness are common emotions in NYC, and what can we do as a community to help each other?
