Analysis and balancing of social network to improve the knowledge flow on multidisciplinary teams

Monclar, Rafael Studart; Oliveira, Jonice; Souza, Jano Moreira de

doi:10.1109/cscwd.2009.4968134

Cited by 11 publications

(4 citation statements)

References 6 publications

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“…Meanwhile, using graph analysis and trust models, many studies have been conducted on visualization [13] and relation maintenance [14][15] and link predictions [16][17] etc., in social networks. In addition, studies intended to apply social networks to diverse areas such as e-mail spam detection [18] and recommendation systems [6][7] have been actively conducted.…”

Section: Related Workmentioning

confidence: 99%

Relational Network Analysis for Advanced National R&D Outcomes Management

Kim¹,

Han²,

Choi³

et al. 2016

IJUNESST

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Section: Related Workmentioning

confidence: 99%

Relational Network Analysis for Advanced National R&D Outcomes Management

Kim¹,

Han²,

Choi³

et al. 2016

IJUNESST

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“…We can also mention the work of [18], who brought the concept of balancing and it was the foundation for the idea presented here. The main difference between the two work, Monclar's focused on a small community of the Department of Systems Engineering and Computing at COPPE/UFRJ, while this work focuses on all the Cancer Control INCT researchers.…”

Section: Related Workmentioning

confidence: 99%

Studying Group Dynamics through Social Networks Analysis in a Medical Community

Albuquerque¹,

Oliveira²,

Faria³

et al. 2014

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In 2008, the Brazilian Department of Science and Technology created the INCTs (Brazilian Science and Technology Institutes). One of them was the Cancer Control INCT. Due to its importance and considering that there are different groups working together in the same area, it is important that they collaborate intensely. Envisioning an empowerment of scientific collaboration, the BRINCA project was created to support a set of analyses of the social networks from this particular INCT. These analyses were created by mining curricular and publications bases, and identifying different types of scientific relationships and areas. We were able to observe, for instance, how the interaction is amongst researchers from related areas, which researchers were more collaborative and which ones were isolated from the network. These analyzes were used by the INCT coordination to understand and act to improve scientific collaboration.

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“…Meanwhile, maintenance and repair methods, using data mining techniques, were proposed to manage the relationship models of dynamic online social networks [32][33][34]. Furthermore, studies on predicting new links between users, which are expected to be formed in the future through existing links, attempted to improve the reliability of relationship models [35][36][37].…”

Section: Related Workmentioning

confidence: 99%

Identity management‐based social trust model for mediating information sharing and privacy enhancement

Kim

Seo

Sang-Hyun

et al. 2011

Security Comm Networks

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As interest in social network studies has grown bigger along with the development of the Web, social network trust management and applications have come into the spotlight. The increasing interest in social network services that are open systems has motivated the need for a reliable trust model that enables practical information sharing and information protection. In this paper, we propose an identity management-based social trust model for solving a sparsity problem and an information leakage. The proposed trust model contributes to increasing the opportunities for information sharing. In addition, the creation and use of identity groups with a clustering approach and partial identities in the proposed approach effectively address security and privacy risks in social networks. In experiments, the performance of the proposed approach is evaluated using precision-recall and F-measures.

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Analysis and balancing of social network to improve the knowledge flow on multidisciplinary teams

Cited by 11 publications

References 6 publications

Relational Network Analysis for Advanced National R&D Outcomes Management

Relational Network Analysis for Advanced National R&D Outcomes Management

Studying Group Dynamics through Social Networks Analysis in a Medical Community

Identity management‐based social trust model for mediating information sharing and privacy enhancement

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