I recently doing sentiment analysis with twitter data stream.
Twitter data stream flowed from real time public Twitter stream which consists of 1% of data of globally tweets flowed to Twitter at given time (by Twitter API docs). Sentiment analysis is to find out the tweets, the information posted by Twitter users, whether it is happy tweet or sad tweet, good tweet or bad tweet, based on some keywords.
I created a simple HTTP interface using Node.JS, ntwitter, sentiment library to archive this objective.
This program can start track some targets keywords, comma separated list of it. Then I can query the current status, how many tweets had been detected. I can then fetch the current Twitter raw data. The last which is the most interesting I can query the sentiment analysis which showing how many percentage there is the positive tweet and negative tweet.
From two days ago I’m trying this, I tried tracking “weather,traffic” and find that most of the KL (Malaysian) and Singaporean always stuck in jam when going works and go back from works, they always complain their own government, but most of the time the sentiment analysis still found that 50:50. Today I will try to test with “Ukraine”, the current sentiment analysis found that the negative is more than positive. I hoped that it will going positive in the next morning :).