What does this AWS Solutions Implementation do?

The Discovering Hot Topics Using Machine Learning solution helps you identify the most dominant topics associated with your products, policies, events, and brands. Implementing this solution helps you react quickly to new growth opportunities, address negative brand associations, and deliver higher levels of customer satisfaction.

The solution uses machine learning algorithms to automate digital asset (text and image) ingestion and perform near real-time inferences using topic modeling, sentiment analysis, entity and key phrase detection, and detection of unsafe images. The solution then visualizes these large-scale customer analyses using a pre-built Amazon QuickSight dashboard.

Discovering Hot Topics using Machine Learning | Sample Dashboard
Sample Amazon QuickSight dashboard
Expand the image to view a sample dominant topic list, donut charts, weekly and monthly trend graphs, word cloud, tweet table, and heat map. The solution also provides the functionality to gather geo coordinate data.
 Click to enlarge

Secure one-click deployment

Provide a secure one-click deployment using an AWS CloudFormation template developed with the AWS Well-Architected Framework methodologies.

Near real-time analytics

Ingest streaming data containing text and images, then analyze them in near real-time. Perform topic modeling to detect dominant topics and identify the terms that collectively form a topic from within customer feedback.

Multi-lingual data ingestion

Use Amazon Translate to ingest data in multiple languages. Identify the sentiment of what customers are saying and use contextual semantic search to understand the nature of online discussions.

Pre-built QuickSight dashboard

Launch the pre-built Amazon QuickSight dashboard to visualize the solution's large-scale customer analyses. Identify insights in near real-time to better understand context, threats, and opportunities almost instantly.

AWS Solutions Implementation overview

The diagram below presents the serverless architecture you can automatically deploy using the solution's implementation guide and accompanying AWS CloudFormation template.

Discovering Hot Topics using Machine Learning | Architecture Diagram
 Click to enlarge

Discovering Hot Topics using Machine Learning solution architecture

The AWS CloudFormation template automatically deploys AWS Lambda functions, Amazon Simple Storage Service (Amazon S3) buckets, Amazon Kinesis Data Streams, Amazon Kinesis Data Firehose, AWS Step Functions workflows, AWS Glue tables, and Amazon QuickSight resources in your account.  

The architecture of the solution includes the following key components:

Ingestion – Social media feed ingestion and management using Lambda functions, Kinesis Data Streams, and Amazon DynamoDB.

Workflow – A Step Functions workflow that orchestrates Amazon Translate, Amazon Comprehend, and Amazon Rekognition.

Inference – AWS machine learning capabilities through Amazon Translate, Amazon Comprehend, and Amazon Rekognition.

Application Integration – Event-driven architecture using Amazon EventBridge.

Storage and Visualization – A combination of Kinesis Data Firehose, Amazon S3 buckets, AWS Glue tables, Amazon Athena, and Amazon QuickSight.

These components are built using the AWS Well-Architected Framework, and the AWS Well-Architected Pillars of Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization—ensuring secure, high-performing, resilient, and efficient infrastructure.

Discovering Hot Topics using Machine Learning

Version 1.4.0
Last updated: 02/2021
Author: AWS

Estimated deployment time: 10 min

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