By Topic

Using social networks analysis for collaboration and team formation identification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Rafael Studart Monclar ; Federal University of Rio of Janeiro (UFRJ), Brazil ; Jonice Oliveira ; Fabricio Firmino de Faria ; Lucas Ventura
more authors

Social networks are sets of links that organize people, groups, and institutions in an equal and democratic way, and around a common purpose [4]. During the formation of such networks, problems can arise, such as elements that concentrate many relationships, very isolated individuals or peripheral members of a network, people who are the only link between two distinct groups, agglomerations of people in isolated points. This can cause a series of communications problems, which ultimately will cause losses to the most important element that flows through social networks: knowledge. Thus it is necessary a series of analysis on social networks so we can monitor possible collaborations and assist in the formation of work teams, this can be done through the concept of balancing social networks developed by us [20], whose main focus is to maintain the social network as cohesive as possible in order to maximize the flow of knowledge. A practical application of these analysis occurred in the project BRINCA (Analysis and Balancing of Scientific Social Networks in Cancer Control). BRINCA's goals are to analyze how members of the Cancer INCT (National Institute of Science and Technology) collaborate and how the scientific knowledge flows amongst the different researchers and institutions. With this project we could perform contextualized analysis (i.e. by relationship type, subject, institution, geographic location, time) and use the metrics of social network analysis to understand and verify how collaboration occurs in a multi-disciplinary, multi-team project. Moreover, we used the criteria of social network analysis to perform the balancing. In addition, some of the analysis made on the scenery of cancer are shown.

Published in:

Computer Supported Cooperative Work in Design (CSCWD), 2011 15th International Conference on

Date of Conference:

8-10 June 2011