Academic Knowledge Transfer in Social Networks
- Author(s): Slater, Mark David
- Advisor(s): Whitehead, James
- et al.
The rise of online social networks has presented many new opportunities and meth- ods for human communication in general and academic communication in particular. Knowledge is created at every level of academia, including individuals, project groups, and research communities. For knowledge to have lasting utility, it must be transferred from one mind to another, for only when knowledge is instantiated in someone's mind can it be used as the base for future action and thought. Today, despite decades of re- search, computer support for knowledge workers in academia is fragmented and poorly integrated. While office automation and other forms of CSCW approaches have ben- efitted academics, no single environment today integrates the basic research activities of the academic knowledge worker, including: individually or collaboratively writing re- search papers, sharing research papers, reviewing papers for publication in a journal or conference and persistently sharing comments and observations on existing literature.
This thesis explores academic knowledge transfer within social networks in several ways. It first presents a model of academic knowledge transfer, along with the requirements for a software system that instantiates that model. The proof-of- concept, named Whisper, for that software system is described, along with the feedback from its users and the changes made to the system's design based on that feedback.
Additionally, an experiment in gamification of knowledge transfer within the Facebook social network is explored, with implications for the knowledge transfer system design. Finally, data from celebrity users and regular users of the Twitter social network is contrasted, providing insight into how often information from the different types of users is re-shared to others, how the "packaging" of that information (a simple statement vs a link to a website) affects the re-sharing rate, and methods users might try to increase the depth their messages can reach in the Twitter network.
Academics currently have very poor tool support for some of the most common tasks they perform, such as organizing the files (both data and research output) across software applications, and linking research output back to the raw data. Both of these concerns, and others, would be addressed by a knowledge sharing environment based on the model described here. The full development of such a system presents additional opportunities for research in human factors, CSCW, and social psychology.