Scientific Community
 The detection of scientific communities aims at improving two main aspects related to scientific research: search (of relevant literature) and assessment (of authors). The detection of communities will mainly help us to evaluate individual productivity and impact with respect to the community itself, that is by
normalizing indexes (e.g. h-index, g-index, and other metrics) with respect to the ones of the community. In this way it is possible to measure interdisciplinary aspects and scope
of research and researchers, narrow down the search domain to the community of
interest, and/or provide diversity of content. The Community Engine Tool was designed to detect community structures on Collaborative Networks. |
Documents
Liquid Pub: Modeling, Managing and Analyzing Scientific Communities Cristhian Parra, Fabio Casati.
In this paper we analyze the problems and challenges in defining and developing a model for scientific communities. We stress the importance of having such communities for providing better search capability and fairer evaluation methods. Finally, we outline some concepts and research directions towards the definition of a conceptual model to support the definition, discovery, maintenance and use of such communities.
Liquid Pub: Scientific Communities Model Cristhian Parra, Fabio Casati.
This paper provides a formal definition of a model for Scientific Communities.
Discovering scientific communities using conference network - Alejandro Mussi
The book presents a complete model and a tool for the detection of scientific communities based on relations between conferences (Degree thesis)
Tools
CET (Community Engine Tool) - We are currently developing a desktop tool to detect scientific communities and then create a Community Network, on which to do several analysis on communities themselves, like impact, productivity, centrality, etc. A preview of the tool is shown on the videos of this page (a beta version of the tool will be available soon on this web site).
Video
Presentations
Detecting Community Structure using CET tool - Alejandro Mussi
Related Work
Structure and Dynamics of Research Collaboration in Computer Science, Bird, Christian and Barr, Earl T. and Nash, Andre and Devanbu, Premkumar T. and Filkov, Vladimir and Su, Zhendong, 2009.
Finding and evaluating community structure in networks, Newman and Girvan,2004
Finding communities in linear time: a physics approach, Fang Wu and Bernardo A. Huberman, 2004
