An algorithm for drawing general undirected graphs
Information Processing Letters
Analysis of SIGMOD's co-authorship graph
ACM SIGMOD Record
Complexity - Understanding Complex Systems: Part II
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
On six degrees of separation in DBLP-DB and more
ACM SIGMOD Record
Co-authorship networks in the digital library research community
Information Processing and Management: an International Journal - Special issue: Infometrics
Collaboration over time: characterizing and modeling network evolution
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
The thematic and citation landscape of Data and Knowledge Engineering (1985-2007)
Data & Knowledge Engineering
Applying Gini coefficient to quantify scientific collaboration in researchers network
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
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We analyze knowledge production in Computer Science by means of coauthorship networks. For this, we consider 30 graduate programs of different regions of the world, being 8 programs in Brazil, 16 in North America (3 in Canada and 13 in the United States), and 6 in Europe (2 in France, 1 in Switzerland and 3 in the United Kingdom). We use a dataset that consists of 176,537 authors and 352,766 publication entries distributed among 2,176 publication venues. The results obtained for different metrics of collaboration social networks indicate the process of knowledge creation has changed differently for each region. Research is increasingly done in teams across different fields of Computer Science. The size of the giant component indicates the existence of isolated collaboration groups in the European network, contrasting to the degree of connectivity found in the Brazilian and North-American counterparts. We also analyzed the temporal evolution of the social networks representing the three regions. The number of authors per paper experienced an increase in a time span of 12 years. We observe that the number of collaborations between authors grows faster than the number of authors, benefiting from the existing network structure. The temporal evolution shows differences between well-established fields, such as Databases and Computer Architecture, and emerging fields, like Bioinformatics and Geoinformatics. The patterns of collaboration analyzed in this paper contribute to an overall understanding of Computer Science research in different geographical regions that could not be achieved without the use of complex networks and a large publication database.