Deploy a solution that helps you identify the most dominant topics associated with your products, policies, events, and brands - Discovering Hot Topics using Machine Learning

Deploy a solution that helps you identify the most dominant topics associated with your products, policies, events, and brands

AWS Solutions Implementation Guide

Publication date: July 2021 (Revisions)

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 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 automates digital asset (text and image) ingestion from Twitter and RSS news feeds to provide near real-time inferences using machine learning algorithms through Amazon Comprehend, Amazon Translate, and Amazon Rekognition to perform topic modeling, sentiment analysis, entity and key phrase detection, and detect any unsafe images. The solution then visualizes these large-scale customer analyses using an Amazon QuickSight dashboard. This guide provides step-by-step instructions for deploying this solution including a pre-built dashboard that provides you with the context and insights necessary to identify trends that help or harm your brand.

This solution provides 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 you identify insights in near real-time: uses a visual dashboard to understand context, threats, and opportunities almost instantly

This solution deploys an AWS CloudFormation template that supports both Twitter and RSS feeds as data source options for ingestion, but the solution can be customized to aggregate other social media platforms and internal enterprise systems.

After you deploy the solution, use the included Amazon QuickSight dashboard to visualize the solution’s machine learning inferences.

Important

For a successful implementation with Twitter as the source, you must create an account and add an App through the Twitter developer portal. For more information refer to Prerequisites.

This implementation guide describes architectural considerations and configuration steps for deploying this solution in the Amazon Web Services (AWS) Cloud. This solution’s AWS CloudFormation template launches and configures the AWS services required to deploy the solution using AWS best practices for security, availability, performance efficiency, and cost optimization.

This solution is intended for deployment in an enterprise by IT infrastructure architects, administrators, and DevOps professionals who have practical experience with the AWS Cloud.