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By Werner Vanzy | Published November 17, 2017 - Updated November 17, 2017
Artificial IntelligenceDatabasesNode.jsCloudHybrid CloudOn PremisesFinanceRetail
Organizations are increasingly interested in their social media profile, and can derive insights into how they are perceived through analysis and classification. This pattern subscribes to Twitter screen names or hashtags and analyzes the content with the Watson™ Tone Analyzer and Natural Language Understanding (NLU), as well as the Watson Assistant API to classify (intents) the tweets. The enriched metadata is then saved to a Cloudant database, where Map Reduce functions are used to provide a high-level insight into the data.
In this pattern, our server application subscribes to a Twitter feed that is configured by the user. Each tweet received is analyzed for emotional tone and sentiment. The intent of the tweet is determined by the Watson Assistant service. All data is stored in a Cloudant® database, with the opportunity to store historical data as well. The information is presented in a Web UI as a series of graphs and charts.
When you complete this pattern, you’ll learn how to:
The setup is done in three primary steps. You will download the code, set up the application, and deploy the code to IBM Cloud. If you would like to run the code locally, there will be one more step to configure the credentials locally.
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