by Shirley Wu
Send Me Love
Last June, SFMOMA launched the SMS-based service Send Me SFMOMA. The initiative was conceived as a way to shed light on the museum’s vast collection, only a fraction of which is on view at any given time. Send Me SFMOMA quickly went viral. SFMOMA partnered with data artist Shirley Wu to create a visualization depicting some of the initiative's more prolific user journeys.
In October 2017, SFMOMA contacted me about an exciting project. It was related to Send Me SFMOMA, a service the museum had recently launched enabling anyone to text a request—“send me love,” “send me hope,” “send me smiles”—and receive back an image of an artwork in the collection that somehow aligns with the request—in its title, content, or otherwise. To date the museum has received more than five million texts from hundreds of thousands of individuals.
They wanted me to do something fun with that data.
The data set was a dream: it was huge, it had interesting attributes, it told stories. As soon as I started exploring, I knew I wanted to focus on individuals. I wanted to highlight their interactions with Send Me SFMOMA: when they texted, what they asked for, what they got back. Bonus points if I could surface how the artwork influenced their mood and what they asked for next. I wondered if I could experience what that person experienced, feel what they felt.
And because I’m terribly cheesy individual, I wanted to create data art from SFMOMA’s art data.
I first went about implementing Tyler Hobb’s’s algorithm for simulating watercolor, and “painting” a stroke for every text that a person ever sent, and coloring it by the artwork they got back. The result, unfortunately, was not very aesthetically appealing.
Then in February 2018, I moved to Tokyo for three months. I could see the anticipation of spring everywhere; every restaurant and café advertised fresh strawberries, subways were filled with adverts picturing spring flowers, and streets were lined with trees turning green again.
I wanted to capture that joy.
I experimented with different flower petal shapes, and colored them with the watercolor effect from earlier. I decided to map each positive request to a flower, and each neutral or negative request to a leaf. I loved how the flowers looked, but I struggled with laying them out in a meaningful way.
In late March, the cherry blossoms started blooming in Tokyo. For a week, every street was pink, and I took extra-long walks after lunch. On one of those walks, I realized that flowers grew on stalks and branches and that would be the most natural way to lay out flowers.
I was immediately happy with how the branches (implemented with a standard binary fractal tree algorithm) brought everything together. The leaves were no longer messily on top of the flowers, and there was instead a sense of order; I could follow the branches and see the texts the individuals sent, and the artworks they got back.
Ultimately I focused my visualization on five individuals—whom I’ve named love, happy, smile, cats, and moon—isolated a week of their interactions so that each tree represents a day in that individual’s life. I loved watching the flowers grow as I re-created their interactions with Send Me SFMOMA. In sifting the little snippets of their lives, I indeed felt what they felt: a tree full of blooming flowers made me wonder what good thing must have happened that day. A tree growing in the early hours of the morning made me feel like I was burning the midnight oil at their side. When I saw a week filled with flowers, then suddenly a small tree with leaves of “mourning” and “black,” I mused on what sad thing had happened.
In the months that I was immersed with this data set, I grew to love it for its beauty and serendipity. And with Send Me Love, I hope to share with others the joy of watching a tree grow and flowers bloom, and of connecting with a perfect stranger over their texts.