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Skip to Main Content View implementation guide The Discovering Hot Topics Using Machine Learning solution identifies the most dominant topics associated with your products, policies, events, and brands. This helps you to react quickly to new growth opportunities, address negative brand associations, and deliver a higher level of customer satisfaction for your business. In addition to helping you understand what your customers are saying about your brand, this solution gives you insights into topics that are relevant to your business. This solution deploys an AWS CloudFormation template to automate data ingestion from these sources: Twitter RSS news feeds YouTube comments tied to videos Reddit (comments from subreddits of interest) Custom data in JSON or XLSX format Using the Reddit API, the solution ingests comments from subreddits of interest. The input parameters to the solution includes a list of subreddits to follow for new comments. The comments then undergo NLP analysis to build the Amazon QuickSight dashboard. Expand the image to learn about how the solution answers the question: What are the most dominant topics related to my product or service? Click to enlarge Provide a secure one-click deployment using an AWS CloudFormation template developed with the AWS Well-Architected Framework methodologies. 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. 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. Launch the pre-built Amazon QuickSight dashboard to visualize the solutions large-scale customer analyses. Identify insights in near real-time to better understand context, threats, and opportunities almost instantly. The diagram below presents the serverless architecture you can automatically deploy using the AWS Solutions implementation guide and accompanying AWS CloudFormation template. Click to enlarge The AWS CloudFormation template automatically deploys AWS Lambda functions, Amazon Simple Storage Service (Amazon S3) buckets, Amazon Kinesis Data Streams, Amazon Simple Queue Service (Amazon SQS) dead-letter-queue (DLQ), 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 and workflows: 1. Ingestion – Social media and RSS feed ingestion and management using Lambda functions, Amazon DynamoDB, and Amazon EventBridge. For detailed reference architecture diagrams for Twitter, YouTube comments, RSS news feeds, and custom ingestion using an Amazon S3 bucket, refer to the implementation guide. 2. Data stream – The data is buffered through Amazon Kinesis Data Streams to provide resiliency and throttle incoming requests. The Data Streams have a configured DLQ to catch any errors in processing feeds. 3. Workflow – Consumer (Lambda function) of the Kinesis Data Streams initiates a Step Functions workflow that orchestrates Amazon Machine Learning capabilities including: Amazon Translate, Amazon Comprehend, and Amazon Rekognition. 4. Integration – The inference data integrates with the storage components through an event-driven architecture using Amazon EventBridge. EventBridge allows further customization to add additional targets by configuring rules. 5. 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. Version: 2.0.0 Last updated: 052022 Author: AWS Estimated deployment time: 10 min Estimated cost Source code Download implementation guide Resources and FAQ » Contact us » Use the button below to subscribe to solution updates. Note: To subscribe to RSS updates, you must have an RSS plug-in enabled for the browser you are using. Did this Solutions Implementation help you? Provide feedback Solving with AWS Solutions: Discovering Hot Topics Using Machine Learning Understanding Voice of Customer with AWS Solutions Discovering Hot Topics Using Machine Learning This blog post teaches readers how to use the Discovering Hot Topics Using Machine Learning solution to draw insights from social media feeds in order to take advantage of rapidly emerging growth opportunities, to address negative sentiment, and to improve customer satisfaction. As an illustration, we walk through a business use case in the Media & Entertainment industry. Read the full blog post Deploy an AWS Solution yourself Browse our library of AWS Solutions to get answers to common architectural problems. Learn more Find an AWS Partner Solution Find AWS Partners to help you get started. Find prescriptive architectural diagrams, sample code, and technical content for common use cases. Learn more
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