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.Read about the methodology and check out the current database of recorded feelings.
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.
Cool as hell. The abovementioned interface is soft, colorful and aesthetically pleasant without being too busy, and it's addicting (I ended up playing with the options for awhile, and admired the design for awhile longer). I found it really interesting to visualize "feelings" this way, especially when taken out of the context of an entry in a personal blog and thrown into the mix with thousands of other random people -- and then sorted, categorized and processed into quantifiable results.
I wonder if I'm in there somewhere. Are you?
0 comment(s):
Post a Comment