Text Mining Virtual Reference through a Collection Management lens: extracting insightful stories and operationalizing data for strategic allocate of resources
Michelle Polchow · 2017
If Google and Facebook are the masters of leveraging big data, consider the impact that institutional specific data might have for libraries to uncover causal relationships and predictive behavior from their user population. George Mason University Libraries applied text mining techniques to analyze 3 years of virtual reference (VR) transcripts. Traditional data management systems are not capable of providing this type of real-time intelligence. The iterative process of analyzing ongoing data may provide management insight into potential misallocation of critical resources, opportunity to better integrate library resources and services, and harvest authentic user conversations with compelling stories to build collaborative campus-wide relationships. This poster provides examples of how data insights might be transformed into actionable business analytics using the collection development lens.