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Social Network Analysis and Mining

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01.11.2011 | Original Article

Development of computer science disciplines: a social network analysis approach

verfasst von: Manh Cuong Pham, Ralf Klamma, Matthias Jarke

Erschienen in: Social Network Analysis and Mining | Ausgabe 4/2011

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Abstract

In contrast to many other scientific disciplines, computer science considers conference publications. Conferences have the advantage of providing fast publication of papers and of bringing researchers together to present and discuss the paper with peers. Previous work on knowledge mapping focused on the map of all sciences or a particular domain based on ISI published Journal Citation Report (JCR). Although this data cover most of the important journals, it lacks computer science conference and workshop proceedings, which results in an imprecise and incomplete analysis of the computer science knowledge. This paper presents an analysis on the computer science knowledge network constructed from all types of publications, aiming at providing a complete view of computer science research. Based on the combination of two important digital libraries (DBLP and CiteSeerX), we study the knowledge network created at journal/conference level using citation linkage, to identify the development of sub-disciplines. We investigate the collaborative and citation behavior of journals/conferences by analyzing the properties of their co-authorship and citation subgraphs. The paper draws several important conclusions. First, conferences constitute social structures that shape the computer science knowledge. Second, computer science is becoming more interdisciplinary. Third, experts are the key success factor for sustainability of journals/conferences.

Vorheriger Artikel Social opinion mining for supporting buyers’ complex decision making: exploratory user study and algorithm comparison

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Titel: Development of computer science disciplines: a social network analysis approach
verfasst von: Manh Cuong Pham
Ralf Klamma
Matthias Jarke
Publikationsdatum: 01.11.2011
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 4/2011
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-011-0024-x

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