Think of a question you have about the world, the simpler the better. Create an experiment that seeks the answer. Design a pilot study that includes gathering data. Consider having a control group and an experimental group to compare. User your data to try and see something that might be invisible to the casual observer.
I wondered if people actually smile or cry on the streets, or if they would explicitly express their feelings in a public space. So I would like to put sensors out on the streets to track individual people that are not in groups, and see if their emotions are easily detectable from their facial expressions.
The best known active emotion sensors are our own eyes, we’ve been trained for years since our very birth to read other people’s facial expressions and to properly respond to it. So I decide to walk outside with my own eyes as the sensor to “scan” the street. I set up some basic rules as follows:
- record only people who walk past me from the front so that I can read their face
- log only people who are alone
- it’s okay to miss a person or two, the sample rate is determined by how fast I write the data down
- avoid crowds and busy streets
It would be great if different aspects of information about the people could be logged together with their facial expression, which might reveal a lot more about why or why not and how people are showing their feelings to strangers. In this case with time and other constraint I decide to record just people’s gender and (rough estimation of) age for cross reporting. By just myself it’s kinda hard to all these things at once, I started by thinking of using devices like vehicle traffic counter but ended up with some simplified logging strategy that helped me also organize the visualization while I was logging.
The data is logged with following rules:
- each circle represents a person
- the vertical position of the circle represents the facial expression: middle for neutral, the top for a big laugh, and the bottom for sad/crying
- horizontal positon is not relevant, although it does loosely represents the time it is logged
- size of the circle represents age, bigger circle is an older person
- circle pattern represents gender, filled circles are female
The completely human powered data visualization looks like below. The data is collected from an approximately 2 hours walk including two subway trips.
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