Social networks play an increasingly important role in knowledge management, information retrieval, and collaboration. In order to leverage the full potential of social networks, social networks need to be supported through technical systems. Within this paper, we introduce such a technical system. It is called AcaSoNet. It is a system for identifying and managing social networks of researchers. In particular, AcaSoNet employs a combination of techniques to extract co-author relationships between researchers and to detect groups of persons with similar interest. Past systems have used either search engines to extract information about social networks from the Web (Web mining) or have required people’s effort to enter their relationships to others into the system (as being done by most social network services). AcaSoNet, instead, uses a combination of these two types, thereby achieving data reliability and scalability. It extracts and collects data of researchers from the Web but allows researchers to modify the data. In the current version, our system can identify the social network based on publication lists and evaluate the publication activities of users within an academic community.
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- A Social Network System for Analyzing Publication Activities of Researchers
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