Presented at the International Sunbelt Social Network Conference, St. Pete Beach, FL (February 2014)
Today’s social network analysis tools provide advanced capabilities that enable experts to analyze and understand the behavior of networks and their constituent entities. Increasingly, non-experts have access to data about network that they can (or should be able to) explore, understand, and leverage (e.g., Facebook, Twitter, LinkedIn). Recently, Facebook released their Graph Search web application which provides a basic version of this type of functionality. Increasingly compelling capabilities for text-based search are sure to arise for users who are not network scientists, but who can benefit from the insights that network science brings to their investigations. Text-based search might let a user ask user-centric questions like, “Who are the best people to follow to learn more about Technology X?” or, “Who among my contacts are emerging as leaders in their careers?” In this presentation, we describe an implementation framework for developing a text-based search capability that incorporates traditional and novel network analysis techniques while providing end-users with an easy-to-use tool for discovering knowledge contained in networks.
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