This is their mission:
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.
The result is a database of several million human feelings, increasing by 15,000 - 20,000 new feelings per day. Using a series of playful interfaces, the feelings can be searched and sorted across a number of demographic slices, offering responses to specific questions like: do Europeans feel sad more often than Americans? Do women feel fat more often than men? Does rainy weather affect how we feel? What are the most representative feelings of female New Yorkers in their 20s? What do people feel right now in Baghdad? What were people feeling on Valentine's Day? Which are the happiest cities in the world? The saddest? And so on.
An interesting website and Jonathan Harris! I think he made another application called Univerce which did a simular thing! Maybe we could look at something like this for creative Tallis!
I love Jonathan Harris' work. You can watch a great video of him talking at one of the TED conferences:
The man's a genius.
Maybe we could collect the emotions of the school over a period of time and present the information in a visual form? Perhaps this could even be mapped on the site. Independent Photography, now called Stream, commissioned a project like this on the peninsula site. I think they used GPS to track locations of people walking around the site and some kind of monitor to measure emotional responses. This then generated an emotional map of the area. here's the link:
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