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Amazon Review Analysis: From Names & Meta Info to Sentiment Analysis
Step 1: Create project & Insert URL
Amazon review analysis with URL
General sentiment overview
2. Automatic topic grouping
5. Improve customer support
To extract meaningful information from any kind of data, ML algorithms need to be able to scan millions of data points. This becomes even more imperative in the case of user-generated content such as customer reviews, which can be highly varied in their structures. AI makes it possible to identify and extract insights from Amazon review analysis seamlessly because it also powers ML algorithms to analyze data at scale and remember data patterns and trends that appear in it.
Sentiment analysis is an intricate process where many ML tasks work methodically to understand and categorize data in order to pinpoint the exact customer sentiment. This happens in mainly three ways, which include diagnostic, predictive, and classifying neutral or ambiguous sentiment.
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