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Sentiment Analysis with Azure Machine Learning


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Sentiment analysis is a special case of text mining that is increasingly important in business intelligence and social media analysis. In this lab, we’ll build an experiment for sentiment analysis of documents in SharePoint, using Microsoft Azure Machine Learning Studio. For example, sentiment analysis of document reviews and comments can help organisations monitor appreciation and utilisation of their IP (Intellectual Property), or help users identify opinion polarity before accessing a resource. This experiment demonstrates the use of the Feature Hashing, Execute R Script and Filter-Based Feature Selection modules to train a sentiment analysis engine. Using a data-driven machine learning approach, document access information and comments are used to train a model using the Two-Class Support Vector Machine, and the trained model is used to predict the opinion polarity of documents in SharePoint sites. The output predictions can be aggregated over document tags containing a certain keyword, in order to find out the overall sentiment for each element of the taxonomy, and lastly published as a Web Service in Azure, for access by third-party applications.

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Sentiment Analysis with Azure Machine Learning

  1. 1. Sentiment Analysis With Azure Machine Learning STEFANO TEMPESTA VP of Engineering, EF Education First, Switzerland @stefanotempesta
  2. 2. AGENDA Sentiment Analysis Text Analytics Azure Machine Learning
  4. 4. Sponsor Raffle!!! • Each sponsor stamp will opt you into their raffle prize and mailings • Collect 9+ sponsor stamps on your Badge to be eligible for the Xbox • Hand entire Badge/ ribbon back into registration desk at end of day • We will draw Badges for prizes at 5pm in Cromwell (if you are drawn and do not have the pre-requisite stamp/s….. You lose!)
  5. 5. Social • Make sure you tweet on #spscambridge or #sqlsatcambridge • During the event we have Giant Jenga, Sack races and Conker Fights! • After event, join us for a post event SharePint/ SQLPint from our bar • Don’t forget to thank Sponsors, Volunteers and Speakers! • The event will close at 6.30pm
  6. 6. Sentiment Analysis “Sentiment Analysis is the process of detecting whether a piece of writing is positive, negative or neutral” • ML-driven Text Mining • Opinion Polarity
  7. 7. Text Analytics Applications: • Product Reviews • Case / Document Classification • Social Media Analytics • Intellectual Property • Plagiarism Check
  8. 8. Text Analytics API Analyze unstructured text for tasks  Language detection  Key phrase extraction  Sentiment analysis Returns a numeric score between 0 and 1  Negative 0 .. 1 Positive sentiment Advanced natural language processing
  9. 9. Application Design Comments Reviews DATASET DASHBOARD User CSOM Import API TEXT ANALYSIS Blob/DB
  10. 10. Azure Machine Learning Import Dataset Model  Train  Score  Evaluate Experiments  Sentiment analysis  Demand estimation  Recommendations  Outcome prediction Publish as Web Service
  11. 11. Azure Machine Learning MODEL REST Service DATASET EXPERIMENT
  12. 12. THANK YOU! /in/stefanotempesta @stefanotempesta