Build Mobile App With Chat
The tutorial uses several Azure services to power a real-time chat infrastructure that is readymade for analytics. Event Hubs ingest chat messages received from websites running in Web Apps. Web Jobs are used to pull chat messages from Event Hubs, invoke the Text Analytics API to apply sentiment scores to each message and to forward messages to Service Bus Topics from which chat participants receive their messages. Stream Analytics is used to drive the archival of scored chat messages into Document DB and Azure Search is used to make the stored chat messages full text searchable.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Build Mobile App With Chat | 26 | 5 years ago | 1 | |||||||
| The tutorial uses several Azure services to power a real-time chat infrastructure that is readymade for analytics. Event Hubs ingest chat messages received from websites running in Web Apps. Web Jobs are used to pull chat messages from Event Hubs, invoke the Text Analytics API to apply sentiment scores to each message and to forward messages to Service Bus Topics from which chat participants receive their messages. Stream Analytics is used to drive the archival of scored chat messages into Document DB and Azure Search is used to make the stored chat messages full text searchable. | ||||||||||
| Hub | 8 | 4 years ago | Java | |||||||
| This is the implementation for KDD 2018 paper "When Sentiment Analysis Meets Social Network: A Holistic User Behavior Modeling in Opinionated Data" | ||||||||||
| Aws Batch Example | 7 | 5 years ago | Java | |||||||
| P7hb Docker Mllib Twitter Sentiment | 5 | 7 years ago | apache-2.0 | Shell | ||||||
| :ship: Docker image for Twitter Sentiment analysis with Spark MLlib | ||||||||||
| Aa Nps Analysis | 5 | 5 years ago | Jupyter Notebook | |||||||
| NPS sentiment analysis | ||||||||||
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