ABSTRACT

Social media channels have become more and more important for many organizations in order to reach targeted groups of individuals as well as understand the needs and behaviors of their users and customers. Huge amounts of social media data are already available and growing rapidly from day to day. The challenge comes in accessing that data and creating usable and actionable insights from it. So far, there are three major approaches that are typically used to analyze social media data: channel reporting tools, overview score-carding systems, and predictive analytics with focus on sentiment analysis. Each has its useful aspects but also its limitations. In this chapter we will discuss a new approach that combines text mining and network analysis to overcome some of the limitations of the standard approaches and create actionable and fact based insights.