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Project Definition - Problem
Motivation:
In the current digital marketplace, customer reviews serve as a primary decision-making driver for consumers and a critical feedback loop for businesses. However, the sheer velocity and volume of incoming data render manual analysis impossible. Consequently, automated Sentiment Analysis has become a fundamental necessity for extracting public opinion at scale.
Problem Definition:
We are looking at Amazon product reviews to classify if sentiment is positive vs negative within Amazon product reviews. The core objective is to predict the polarity of a review based solely on its textual content.
Technical Challenge:
Reviews are unstructured text data. They contain slang, typos, varying lengths, and mixed signals. We need a way to mathematically represent this text and classify its polarity (positive vs. negative) accurately and at scale.