How to Make Applications Discern Meaningful Insights from Social Media and Human-Generated Content
Human-generated content encompasses latent actionable knowledge that can be leveraged to spectacular business benefit. Yet the challenge to gaining business advantage from the use of social media data lies in facilitating discovery and exploitation: finding technologies that can process unstructured or semi-structured social media data, blend it with data from conventional relational databases and data warehouses, enterprise transactional systems, or customer relationship management (CRM) data, and then enable its interpretation and organization so that it can inform decision-making. And much like precious metals lying buried deep in the earth, the value of the nuggets of insight buried within human-generated content can only be actualized if that value exceeds the cost of extraction, a process that often remains the barrier to integrating social media into any system or application.
This report explores the innovative uses of social media data and how working with that data is both relevant and accessible in the context of enterprise development. We discuss the main challenges of integration and explore the mechanics for extracting relevant “signal” from the rest of the social media “noise” to suit the needs of the enterprise.