Sentiment Analysis using AWS Comprehend & Lambda

Design a serverless sentiment analysis system leveraging AWS services.

Requirement

Gather the input text (that could be a comment or a feedback on a survey, etc) and feed it into a compute service that figures out the sentiment from the text.

Design Solution

Glossary

SQS: It is a managed message queuing service that lets enables us to decouple and scale serverless applications by sending, storing, and receiving messages.

Lambda: It is a serverless compute service that allows us to run code without managing servers and worrying about scaling.

Comprehend: It is an NLP service that helps us extract key phrases, sentiment, PII, syntax, entities, identify language, and more.

Implementation Plan

• An SQS queue that stores messages and triggers Lambda function.
• The Lambda function processes the message body and invokes Comprehend to infer the sentiment from the text.
• Finally the Lambda function stores the text and inferred sentiment into a table in RDS.

Here’s the Github link for the above design & code: https://github.com/anmol111pal/Sentiment-Analyzer

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