Sentiment Analysis with Big Data
Duration: 60 minutes
Track: Big Data & Azure
People’s sentiments and opinions are written in social networks. There are tweets, Facebook posts, book reviews, forum discussions, and more. These attitudes and feelings are communicated using text, with format depending on the social network. Twitter messages are limited to 140 characters and use hash-tags,; Facebook messages can be longer. This session reviews the different Natural Language Processing, text mining, and data mining techniques you can use for sentiment and tone analysis. Organizations can use the extracted knowledge for brand reputation, market predictions, and automatic learning. We’ll look at, Hadoop, data mining, Microsoft Big Data Hadoop distribution HDInsight and Azure Machine Learning
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