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Social Business Intelligence with IBM Social Media Analytics

Social Business Intelligence with IBM Social Media Analytics

There is no shortage of opinions on the Internet, including opinions about your products and services. Collecting information about those opinions has been difficult. Natural language texts, like reviews, blog posts, and various forms of social media commentary, do not lend themselves to the traditional collect, transform and analyze techniques we use with more structured data. 

Two broad approaches are available for analyzing social media text: text analytics and natural language processing. Both have a role in social media analytics but it is important to understand the benefits and drawbacks of both. 

This article outlines key features to look for in social media analysis tools such as IBM Social Media Analytics, which includes support for both types of language analysis.

Dan Sullivan is an author, systems architect, and consultant with over 20 years of IT experience with engagements in systems architecture, enterprise security, advanced analytics and business intelligence. He has worked in a broad range of industries, including financial services, manufacturing, pharmaceuticals, software development, government, retail, gas and oil production, power generation, life sciences, and education.  Dan has written 16 books and numerous articles and white papers about topics ranging from data warehousing, cloud computing and advanced analytics to security management, collaboration, and text mining.

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