Mining and analyzing organizational social networks for collaborative design

Silva, Ricardo; Menezes, Victor Ströele A.; Oliveira, Jonice; Souza, Moises Ferreira de; Mello, Carlos E.; Souza, Jano Moreira de; Zimbrão, Geraldo

doi:10.1109/cscwd.2009.4968109

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…In analyzing the results obtained with this new algorithm we saw that the number of Unit Groups was reduced, i.e., the number of groups formed by only one researcher decreased considerably. In the previous work [25,30] we found ten Unit Groups and, when using the algorithm that analyzes the network flow in this work we found only two. Table 1 was built based on Figure 5 and shows group distribution within and amongst institutions.…”

Section: A Clustering Analysismentioning

confidence: 83%

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Evaluating knowledge flow in multirelational scientific social networks

Ströele

Zimbrão

Souza

2011

Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

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Social networks are dynamic social structures consisting of individuals or organizations, usually represented by nodes tied by one or more types of relationships. Analyzing these structures allows us to detect several inter and intra connections between people, inside and outside their organizations. In this context, we construct a multi-relational scientific social network where researchers may have four different types of relationships with each other. Using clustering techniques with max flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific scenario of the Computing Sciences.

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Section: A Clustering Analysismentioning

confidence: 83%

“…In previous studies [25,30] we used an algorithm to detect clusters using a minimum spanning tree. This method uses both the profile data and the information on relationships during the clustering process.…”

Section: A Relationships As Similarity Metricmentioning

confidence: 99%