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This lab explores text analytics and R integration with Azure Machine Learning. It will walk through loading data from an external source, using R scripts in ML Studio, and common text analytics tasks and visualizations.
Social media has become a very influential platform for companies, consumers, and professionals to express ideas and opinions, market new products and advertise sales, or share any other important news and information. Most social media sites include keywords or hashtags users can post related content to. If companies can access and perform advanced analytics on the keyword posts that are relevant to them, they can learn things such as customer sentiment, related products and companies, and who is buying products and where from. For this lab, you will be working with real Twitter data pulled from a Twitter API. The data includes real Tweets that used the hashtag, Azure. The R language has an expansive collection of packages and functions for advanced text mining and analytics. The lab will use R scripts that will be executed in ML Studio. These scripts will perform data preparation, exploration, and visualization tasks common to text mining. The end result will be a visualization that provides context to frequently used terms in the analyzed Tweets.