Sep 27, 2000
The Structure of Scientific Collaboration Networks
Dr. Mark Newman, Center for Applied Mathematics, Cornell University & Santa Fe Institute
The study of social networks -- maps of who knows whom -- has been hampered by the poor
quality of the available data, which are mostly derived from field interviews in specific
communities. In this talk, I will describe recent work, both empirical and theoretical,
on the study of a large network for which the data are numerous and accurate, and
which is of direct interest to us in academia; the network of collaborations between
scientists, as revealed by the papers they write. Assuming two scientists to be
connected if they have written a paper together, we have analyzed a number of large
computer databases of publications to construct explicit networks and used these
networks to answer questions like: Who are the best connected scientists in the world?
Which scientists have the strongest collaborations? Which scientists connect most
others together? HOw many "degrees of separation" are there between scientists on
average? And what differences are there between collaboration networks in different
disciplines? We have also constructed some exactly solvaable graph theoretical models
of collaboration networks, which can help us to understand hwo much of what we see in
our networks is just the result of random chance, and how much of it comes about through
social interactions between scientists.
Audio for this talk requires sound hardware, and RealPlayer or RealAudio
Begin continuous audio for the whole talk:
high bandwidth or low bandwidth.
(Or, right-click to download the whole audio file.)
To begin viewing slides, click on the first slide below.
Author entry (protected)