Sentimental Analysis : PART 1
Sentimental Analysis refers to identify, extract, quantify, and study affective states and subjective information. It helps to identify public emotion about certain topics/products. Humans are fairly intuitive when it comes to interpreting the tone of a piece of writing, but teaching a machine to identify emotion is tough. A negative sentence can be assumed by machine as positive. For example, In case of sarcastic sentence "I have lost my watch again. That's brilliant", humans can easily tell that it's a negative emotion framed in sarcasm but machine can assume that it's a positive sentence without knowing the context. Applying the contextual information, machine can identify it to be negative emotion. Sentimental Analysis helps to gain insight from social data and to understand the consumer attitude and act accordingly. VOC(Voice Of The Customer) applications are primarily used by companies to determine what a customer is saying about a product o