While playing with some collective intelligence techniques under the Twitter, i and some friends developed a simple application with the original idea of my friend Bruno Melo and some suggestions of my friend Ricardo Caspirro to count the number of retweets that you do on twitter and the users that you most retweet. We decided to give it the name of BabaOvo (A portuguese word that means that you are a pamper or flatter) . The idea is to know how many retweets i've done in all my statuses profile and whose the users i retweeted (RT) most.
The code is so simple and we've done it all in Python! Soon i'll release a official version and the source code so you can you it on your own.
I've made a test with my twitter username 'marcelcaraciolo' , and i've discovered some really interesting insights: ' I like the user lucianans (hehhe she's my date)' , 'The users cinlug, larryolj and the user tarantulae are related to python development and open-source: what i like a lot' . 'marcelobarros, telmo_mota, croozeus are associated with mobile topics: great guys to follow if you want to know about mobile area' and at least 'reciferock, davidsonFellipe and macmagazine: all personal interests: rock music, blogs and the apple world' !
It's amazing what you can find about you only using this simple technique of text mining ! Data mining is a powerful area and natural language processing is incredible if you know how to handle it. I am playing with it and soon i'll publish here some results of a project that i am doing with recommendations and Twitter networking!
For now, take a look on the pie chart that i plot after running the babaOvo application. I've put only the top-10 users! The chart was drawn with the Matplotlib Python framework!
BabaOvo Pie Chart : Frequency Retweets