What does this AWS Solutions Implementation do?
The Discovering Hot Topics Using Machine Learning solution helps businesses identify the most dominant topics associated with their products, policies, events, and brands. It uses machine learning algorithms to automate digital asset (text and image) ingestion and perform near real-time topic modeling, sentiment analysis, and image detection. The solution then visualizes these large-scale customer analyses using an Amazon QuickSight dashboard that provides customers with the context and insights necessary to identify trends that may help or harm their brand. By leveraging this comprehensive visibility into customer sentiment and conversations, businesses can react quickly to new growth opportunities, address negative brand associations, and deliver higher levels of customer satisfaction.
The solution performs the following key features:
- Performs topic modeling to detect dominant topics: identifies the terms that collectively form a topic from within customer feedback
- Identifies the sentiment of what customers are saying: uses contextual semantic search to understand the nature of online discussions
- Determines if images associated with your brand contain unsafe content: detects unsafe and negative imagery in content
- Helps customers identify insights in near real-time: uses a visualization dashboard to better understand context, threats, and opportunities almost instantly
Version 1.0.0 of the solution deploys an AWS CloudFormation template that supports Twitter as the default data source, but the solution can be customized to aggregate other social media platforms and internal enterprise systems.
After you deploy the solution, you can use Amazon QuickSight to build a visualization dashboard to display the solution’s machine learning inferences. The image to the right is an example visualization dashboard. The first row of visuals in the dashboard shows the aggregation of all the dominant topics detected, and the second row drills down to the most dominant topic '000'. The bottom left corner of the image demonstrates that selecting a specific phrase (in this example, machinelearning) in the word cloud filters the data for the related donut chart and table.
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 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, and AWS Glue tables 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.
Inference – AWS machine learning capabilities through Amazon Translate, Amazon Comprehend, and Amazon Rekognition.
Application Integration – Event-driven architecture using AWS EventBridge.
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.
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Near real-time analytics
Multi-lingual data ingestion
Secure one-click deployment
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