REAL-TIME DATA PROCESSING WITH STORM: USING TWITTER STREAMING

In today's highly developed world, every minute, people around the globe express themselves via various platforms on the Web. And in each minute, a huge amount of unstructured data is generated. Such data is termed as big data. User opinions are related to a wide range of topics like politics, latest gadgets and products. Here we propose to analyze the sentiments of Twitter users through their tweets in order to extract what they think. We classify their sentiments into three different polarities – “positive”, “negative” and “neutral.” Since, 6000 tweets are generated every second and this number is increasing, we need a robust system to process these tweets in real-time. Here, batch-processing would have its limitations and therefore a real-time and fault tolerant system, Apache Storm is used. This process as a whole is also called as Opinion Mining or voice of the customer