By: |
Alireza Abbasi;
Jorn Altmann (Technology Management, Economics and Policy Program (TEMEP), Seoul National University) |
Abstract: |
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. |
Keywords: |
Social network systems, academic community, co-author relationship, publication analysis, productivity analysis, knowledge sharing, knowledge transfer, Web mining, performance analysis, and social network analysis. |
JEL: |
C43 C88 D83 L86 |
Date: |
2010–04 |
URL: |
http://d.repec.org/n?u=RePEc:snv:dp2009:201058&r=ict |