Twitter Sentiment Analysis using Hadoop on Windows
This is a demonstration based session which will show how to use a HDInsight (Apache Hadoop exposed as an Azure Service) cluster to do sentiment analysis from live Twitter feeds on a specific keyword or brand. Sentiment analysis is parsing unstructured data that represents opinions, emotions, and attitudes contained in sources such as social media posts, blogs, online product reviews, and customer support interactions. The demo uses Hadoop Hive and MapReduce to schematize, refine and transform raw Twitter data. It will also focuses on the Hive endpoint that HDInsight exposes for client applications to consume HDInsight data through the Hive ODBC interface. Finally, this session will show the present day self-service BI tools (Power View, Power Query and Power Map) to demonstrate how you can generate powerful and interactive visualization on your twitter data to enhance your brand promotion/productivity with just a few mouse clicks.
This is a demonstration based session which will show how to use a HDInsight (Apache Hadoop exposed as an Azure Service) cluster to do sentiment analysis from live Twitter feeds on a specific keyword or brand. Sentiment analysis is parsing unstructured data that represents opinions, emotions, and attitudes contained in sources such as social media posts, blogs, online product reviews, and customer support interactions. The demo uses Hadoop Hive and MapReduce to schematize, refine and transform raw Twitter data. It will also focuses on the Hive endpoint that HDInsight exposes for client applications to consume HDInsight data through the Hive ODBC interface. Finally, this session will show the present day self-service BI tools (Power View, Power Query and Power Map) to demonstrate how you can generate powerful and interactive visualization on your twitter data to enhance your brand promotion/productivity with just a few mouse clicks.
- Type of material
- Terms of use
- Target audience
- Subject areas
- Languages
- Media formats
- Accessibility features
- Other metadata
- author: Debarchan Sarkar
- OER type
- Metadata and online reference
- Source repository
Submitted by
Marco Montanari
on 25/11/2015
in the project IWS Novembre 2015
Last updated on 29/11/2015
- Evaluations
- No evaluation
Please log in to add evaluation.


No comments yet.
Please log in to leave a comment.