Co-authorship networks are examples of social networks, in which researchers are linked by their joint publications. Like many other instances of social networks, co-authorship networks contain rich sets of valuable data. In this paper, we propose a visual analytic tool, called SocialVis, to analyze and visualize these networks. In particular, SocialVis first applies frequent pattern mining to discover implicit, previously unknown and potential useful social information such as teams of multiple frequently collaborating researchers, their composition, and their collaboration frequency. SocialVis then uses a visual representation to present the mined social information so as to help users get a better understanding of the networks.
%0 Conference Paper
%1 leung2011visual
%A Leung, Carson Kai-Sang
%A Carmichael, Christopher L.
%A Teh, Eu Wern
%B HCII (FAC) 2011
%D 2011
%E Schmorrow, Dylan D.
%E Fidopiastis, Cali M.
%I Springer
%K analytics mining networks social visual
%P 335-345
%T Visual analytics of social networks: mining and visualizing co-authorship networks
%U http://dx.doi.org/10.1007/978-3-642-21852-1_40
%V 6780
%X Co-authorship networks are examples of social networks, in which researchers are linked by their joint publications. Like many other instances of social networks, co-authorship networks contain rich sets of valuable data. In this paper, we propose a visual analytic tool, called SocialVis, to analyze and visualize these networks. In particular, SocialVis first applies frequent pattern mining to discover implicit, previously unknown and potential useful social information such as teams of multiple frequently collaborating researchers, their composition, and their collaboration frequency. SocialVis then uses a visual representation to present the mined social information so as to help users get a better understanding of the networks.
@inproceedings{leung2011visual,
abstract = {Co-authorship networks are examples of social networks, in which researchers are linked by their joint publications. Like many other instances of social networks, co-authorship networks contain rich sets of valuable data. In this paper, we propose a visual analytic tool, called SocialVis, to analyze and visualize these networks. In particular, SocialVis first applies frequent pattern mining to discover implicit, previously unknown and potential useful social information such as teams of multiple frequently collaborating researchers, their composition, and their collaboration frequency. SocialVis then uses a visual representation to present the mined social information so as to help users get a better understanding of the networks.},
added-at = {2014-03-24T20:22:31.000+0100},
author = {Leung, Carson Kai-Sang and Carmichael, Christopher L. and Teh, Eu Wern},
biburl = {https://www.bibsonomy.org/bibtex/22371b8c819a990e3afeb09fd0c60e315/kleung},
booktitle = {HCII (FAC) 2011},
editor = {Schmorrow, Dylan D. and Fidopiastis, Cali M.},
interhash = {3e9c53e46411fc249be3435446d5eb3b},
intrahash = {2371b8c819a990e3afeb09fd0c60e315},
keywords = {analytics mining networks social visual},
month = jul,
pages = {335-345},
publisher = {Springer},
series = {LNAI},
timestamp = {2014-03-24T21:01:07.000+0100},
title = {Visual analytics of social networks: mining and visualizing co-authorship networks},
url = {http://dx.doi.org/10.1007/978-3-642-21852-1_40},
volume = 6780,
year = 2011
}