Get an outline of a blueprint for the social media sentiment analysis use case and identify individual modules, their responsibilities, and interactions with each other.
- Let us now outline a solution…for social media sentiment analysis…to make sure we can handle complaints in real time.…We first start with Twitter.…Twitter provides a real-time streaming API…that can be used to listen to tweets happening…for a specific user, handle or hashtag.…We need a real-time subscriber…that will subscribe to Twitter…and receive tweets coming in for specific hashtags…related to your company's products.…
The tweets received will then be converted…to a standardized format and pushed into a streaming queue.…Facebook, similarly, has a real-time streaming API.…We need a real-time subscriber for Facebook…which will receive Facebook posts,…convert it to the same standardized format…and push it to the same queue.…This is an extensible model.…Almost all social media platforms, like Instagram…and Gooogle Plus, support streaming interfaces…and we can add similar subscribers…to those also in the future.…
A text mining engine is required…to de-queue the posts in real-time from the queue.…This engine will cleanse the post text…
There is no coding involved. Instead you will see how big data tools can help solve some of the most complex challenges for businesses that generate, store, and analyze large amounts of data. The use cases are drawn from a variety of industries, including ecommerce and IT. Instructor Kumaran Ponnambalam shows how to analyze a problem, draw an architectural outline, choose the right technologies, and finalize the solution. After each use case, he reviews related best practices for real-time streaming, predictive analytics, parallel processing, and pipeline management. Each lesson is rich in practical techniques and insights from a developer who has experienced the benefits and shortcomings of these technologies firsthand.
- Components of a big data application
- Big data app development strategies
- Use cases: fraud detection and product recommendations
- Technology options
- Designing solutions
- Best practices