How do you test an application which constantly listens to the customers, learns their behaviour and create personalised engagements based out of learnings!!
Today data plays a vital role in every decision making and hence making sense of the data to derive useful insights for our customers is a key for success.
Sentiment Analysis is the process of classifying the data into positive, negative or neutral implemented using natural language processing (NLP) and Machine Learning techniques that helps in analysing the data to gauge public opinion, market research, monitor brand and product reputation, and understand customer experiences and is mostly offered as Sentiment Analysis as-a-Service .
In this talk we will discuss the Challenges are around analysing, explicit and implict opinions, sarcasm, comparative opinions, Multilingual, Emojis, defination on neutral to just name a few and the strategies to test such applications with a use case on Airlines Sentiment (trained with tweets about airlines to identify between positive, neutral, and negative tweets).