Visual Experiments with Neighborhood Data

I’m taking a week to put together quick, creative experiments and visualizations of real-time urban data and recent social media from San Francisco’s Mission District. I’m looking at the data in playful ways to make observations about the urban environment. I will see which observations and layers resonate with users and make these the ground rules for the generative art.

Color

Here’s a map of the most dominate colors of Instagram photos taken in the Mission.

pointalism

Here’s the same data with a blur:
blur
Here’s a heat map of photos with the color green. Not surprisingly, there’s a bunch of photos in Dolores Park.
Cursor_and_CodePen_-_Colors_from_Photos_Taken_in_the_Mission

Now, what if we took these colors and used to paint buildings in the neighborhood. I’ll use more vibrant colors to represent more dense areas.

painted-buildings

Or I can take a subset of hues:
CodePen_-_Painting_Building_with_Social_Colorunnamed

Words & Symbols

I’m analyzing social media for parts of speech, such as Adjectives, Proper Nouns, Adverbs, and non-English words. I’m looking at these words over all time or during the small time frame like the last hour or last day.

Activities Example

One promising way to filter post related to activity is to look for the gerund form of verbs.

Here’s a snapshot of activity from earlier in the day. I realized the style of labels is reminiscent of magnetic poetry although that was not my original intent.

activity
Here’s a more active time of day:
activity-density

The top 10 gerunds over the past two weeks are:

  1. Going
  2. Looking
  3. Working
  4. Making
  5. Coming
  6. Taking
  7. Drinking
  8. Living
  9. Eating
  10. Buying

There are also some popular activities I wouldn’t have thought of:

  • Vaping is quite popular
  • Fursuiting is popular too. Urban Dictionary defines this activity as “a style of costuming that focuses on animal costumes. Fursuiting events include costume parades and dances at conventions, charity and other public events, mascot competitions, and fursuit bowling.”

I can filter this data to particular types of activities. Here’s where people have likely been eating, drinking, and shopping:
CodePen_-_Eating__Drinking__Shopping

Or maybe look at where people work vs. play:
CodePen_-_Eating__Drinking__Shopping

Places

The places that people most frequently mention are San Francisco, Oakland, Dolores Park, Mission St. Castro, Valencia, the Chapel, Clubs, Galleries, and Theatres.

Here’s a map of the most recent Emoticons used in Twitter and Instagram posts:
emojis

How could these visual be included in my final project?

Here are some ideas for how these could be included in a final piece at Gray Area theater.

  • Buses that pick up words and symbols from bus stops
  • Madlibs or Spatial Magnetic poetry
  • Buildings that get painted with color
  • Fog that carries emotions
  • Buses or Fog that act as a flashlight to other data
  • Auto-generated headlines from parts of speech
  • Adverbs to express movement
  • Adjectives to express feeling
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