Film Futurist

With the popularity of Twitter, Facebook status updates, one expects to see all manner of ideas useful and useless, swirling around these platforms and vying for our attention. so it was no surprise when Mashable ran a piece last month on Twitter Art.  The ideas tend to revolve around the age-old putting visuals-to-text using — what else — Twitter and Flickr. Creators like Twitter Mosaic and Portwiture use algorithms which select images randomly or from a specific pool of images related to words in your Twitter feed. These random selections produce what essentially looks like visual/text wallpaper. Interesting, but essentially they are creating superficial connections with varying and often random relationships.

In surveying the various projects out there, I found myself drawn to Twistori, which is an interesting take on this  trend. By limiting their tracking to only real time uses of the words LOVE, HATE, THINK, BELIEVE, FEEL and WISH, the project draws your attention to the verbs that create human emotion. Below, I have simply screen-grabbed whatever came through the feed in the 2-3 minutes span I was watching it scroll through.

The makers of this project acknowledge that their inspiration comes from another project called We Feel Fine which actually tracked emotions mined from all over the web in the form of text and image, and then organized them into a fascinating compilation and creative analysis of human feelings. It took me a while to wrap my head around what they were actually doing. I should say that the the authors of the project Jonathan Harris and Sep Kamvar, are together a combination of computational, creative and sociological whizkiddery. But don’t let that deter you from looking through this project, and apparently their soon-to-be-published book on the project. In their explanation of the project and its methodology they say:

Since August 2005, We Feel Fine has been harvesting human feelings from a large number of weblogs. Every few minutes, the system searches the world’s newly posted blog entries for occurrences of the phrases “I feel” and “I am feeling”. When it finds such a phrase, it records the full sentence, up to the period, and identifies the “feeling” expressed in that sentence (e.g. sad, happy, depressed, etc.). Because blogs are structured in largely standard ways, the age, gender, and geographical location of the author can often be extracted and saved along with the sentence, as can the local weather conditions at the time the sentence was written. All of this information is saved.

I surmised after reading through their material, that they are in fact going about storytelling in a quasi-scientific way – and I say “quasi” only because while data is real, what they are seeking to document is really the range of human emotion.  So while they do uncover patterns in people’s feelings/behavior, it never quite seems that the purpose of the project is purely statistical despite their use of all this computational skill and technology.

There are fascinating ideas in the individual words and images here and it begs the question, “where does science/technology meet art and storytelling”?

The conversation continues.