185,252 research outputs found
The Structure of Scientific Collaboration Networks in Scientometrics
No full textThe structure of scientific collaboration networks in scientometrics was investigated at the level of individuals by using bibliographic data of all papers published in the international journal Scientometrics retrieved from the Science Citation Index (SCI) during 1978 to 2004. Combined analysis of social network analysis (SNA), co-occurrence analysis, cluster analysis and frequency analysis of words was explored to reveal: (1) The microstructure of the collaboration network on scientists’ aspects of scientometrics; (2) The major collaborative fields of the collaborative sub-networks; (3) The collaborative center of the collaboration network in scientometrics
Collaboration in Iranian Scientific Publications
No full textThis study looks at international collaboration in Iranian scientific publications through the ISI Science Citation Index® (SCI) for the years 1995-1999, inclusive. These results are compared to and contrasted with the earlier findings for the periods covering 1985-1994 (Osareh & Wilson 2000). The results of Iran's increasing productivity over a 15-year period are presented. Iran doubled its output in the first two five-year periods and increased 2.8-fold from the second to the third five-year period. The rise in Iran's scientific publication output is due mainly to factors such as the ending of the war, better economic conditions, recent changes in the Iranian government's policy, basic changes in the political environment brought about by the Reformers, expansion of the Iranian presses for national publications, and the recent return of a large number of students trained overseas through government scholarships. External changes also account for the increased productivity, e.g., the acceptance of three Iranian source journals by the SCI, increased access to international databases through the Internet and better electronic communication facilities for international collaboration. One of the most important and significant factors that caused this dramatic rise seems to be the government's research policies in the last few years. Since 1999, the Iran Science, Research and Technology Ministry, has encouraged researchers to publish their non-Farsi language articles in highly ranked international scientific journals, for example, by giving prizes to researchers who publish their articles in ISI-ranked journals
Inter-institutional scientific collaboration: an approach from social network
No full textThis paper presents a tool that can be used to characterize, analyze and interpret the
patterns of collaboration among institutions by means of the visual display of scientific
information. These graphic representations allow for a combined analysis of a given
institution in the system of relations (network), and of the particular attributes of that
institution (indicators). The tool affords the possibility of regenerating the network to
make any number of aggregates appear or disappear, thus allowing one to focus on
institutional sectors, geographic regions, etc. It also allows for analysis of sectorial
interaction, institutional backing of research, and the influence of geographic proximity,
linguistic affinity, or regional politics. This is indeed a versatile analytical tool, and it is
bound to prove its potential for evaluating patterns of collaborative research, development
and innovation
New approach to the visualization of international scientific collaboration
No full textIn this study, visual representations are created in order to analyze different aspects of scientific collaboration at the international level. The main objective is to identify the international facet of research by following the flow of knowledge as expressed by the number of scientific publications, and then
establishes the main geographical axes of output, showing the interrelationships of the domain, the intensity of these relations, and howthe different types of collaboration are reflected in terms of visibility. Thus, the methodology has a twofold application, allowing us to detect significant differences that help
characterize patterns of behaviour of a geographical system of output, along with the generation of representations that serve as interfaces for domain analysis and information retrieval
The Geographical and Institutional Proximity of Scientific Collaboration Networks
No full textThe geography of innovation has established itself as a central subject in economic geography. Geographical proximity to firms and organizations like universities is supposed to have a positive effect on a firms’ innovative performance. One of the reasons causing these positive agglomeration effects is the fact that collaboration is eased by geographical proximity. Although the role of proximity for collaboration is a well researched theme with regard to innovation, less is known about the role of proximity in scientific collaboration and how this affects the probability and nature of networking among research institutions. This is surprising given the fact that collaboration in science has become a central policy issue. In this paper we set out a number of theoretical considerations about the role of geography for innovation and see whether these apply for science as well. The empirical part will focus on the geography of collaboration in scientific knowledge production, testing the hypothesis that collaboration between different kinds of organizations is geographically more localized than collaboration between the same kinds of organizations due to institutional or organizational proximity. Besides this we will analyze the importance of spatial proximity for various forms of collaboration (such as university-university and university-firm collaboration) using the concept of the gravity model. Finally we will look at the spatial structure of these collaboration networks using insights from social network methodology. Based on co-publications, central nodes of collaborative interaction and network structures are analysed over time. On the network-level we conclude on differences in the fields of life- and physical sciences and on differences on the type of relations according to university-firm, university-university and university-governmental institution linkages. On the regional level we conclude on the centrality and spatial extent of scientific collaboration hubs over time
Co-authorship Network of Scientometrics Research Collaboration
No full textThis paper examines the co-authorship network in the field of scientometrics using social network analysis techniques with the aim of developing an understanding of research collaboration in this scientific community. Using co-authorship data from 3125 articles published in the journal Scientometrics with a time span of more than three decades (1980-2012), we construct an evolving co-authorship network and calculate three centrality measures (closeness, betweenness, and degree) for 3024 authors, 1207 institutions, 68 countries and 22 academic fields in this network. This paper also discusses the usability of centrality measures in author ranking, and suggests that centrality measures can be useful indicators for impact analysis. Findings revealed that scientometrics was not dominated by a couple of key researchers as quite a significant number of popular researchers were identified. The United States occupies the topmost position in all measures except for degree centrality. The most active, central and collaborative academic discipline in scientometrics is Information & Library Science
The methodological status of co-authorship networks
No full textA powerful strategy within the study of collaboration
in science is to posit that co-authorship patterns
represent social networks.
It is prerequisite to an application of Social
Network Analysis (SNA) to define the network
entities. A network analysis of the inter-institutional
collaboration in COLLNET on the basis
of co-authorships was conducted. The study reveals
that it is crucial whether the co-authorship
itself is seen as an author's relational property or
as a social event that brings the authors together.
The former possibility is represented by a onemode
network in which each author can be related
to each other author. Quite distinct from
that are two-mode networks, the latter approach.
They consist of two single data sets in which relations
are only possible between different sets.
Different modes of representations require
different network approaches. One is that co-authorship
networks are seen as one-mode networks,
which has the advantage of the application
of a variety of measures. In contrast, twomode
networks, the other option, cannot be analysed
by standard techniques but its distinctive
features demand a new conceptualisation of
measures. In conclusion, the two-mode perspective
is more promising because it allows a dual
perspective on collaboration in science which includes
researchers as well as their scientific output
Visual display of international scientific collaboration networks
No full textThis study shows visual displays of scientific information from which different aspects of international collaboration may be analyzed. The first aim is to identify the degree of “internationality” of research by highlighting fluxes of knowledge in the form of publications. This allows us, in turn, to identify the main geographical axes, to show the relationships of the analyzed domains with other countries, discovering the relative strength of these relations, and to see how they might affect the visibility of the work on the virtual horizon. Two final applications are foreseen: the detection of significant differences that can help to characterize the publishing patterns of a given geographical domain or system of knowledge interchange, and the generation of visualizations that act as interfaces for domain analysis in general
Visualization of scientific co-authorship in Spanish universities : From regionalization to internationalization
No full textPurpose – The purpose of this paper is to visualize the inter-university and international collaboration networks generated by Spanish universities based on the co-authorship of scientific articles.
Design/methodology/approach – The approach takes the form of formulation based on a bibliometric analysis of Spanish university production from 2000 to 2004 as contained in Web of Science databases, applying social network visualization techniques. The co-authorship data used were extracted with the total counting method from a database containing 100,710 papers.
Findings – Spanish inter-university collaboration patterns appear to be influenced by both geographic proximity and administrative and political affiliation. Inter-regional co-authorship encompasses regional sub-networks whose spatial scope conforms rather closely with Spanish geopolitical divisions. Papers involving international collaboration are written primarily with European Union and North and Latin American researchers. Greater visibility is attained with international co-authorship than with any other type of collaboration studied.
Research limitations/implications – Impact was measured in terms of journals rather than each individual paper. The co-authorship data were taken from the Web of Knowledge and were not compared with data from other databases.
Practical implications – The data obtained in the paper may provide guidance for public policy makers seeking to enhance and intensify the internationalization of scientific production in Spanish universities.
Originality/value – The Spanish university system is in the midst of profound structural change. This is the first paper to describe Spanish university collaboration networks using social network visualization techniques, covering an area not previously addressed.
Paper type Research pape
Measuring author influence in scientific collaboration networks
No full text
Purpose: The purpose of this paper is to measure author influence in scientific collaboration networks by considering the combined effects of multiple indexes. In the meanwhile, we intend to explore a method to avoid assigning subjective weights.
Design/methodology/approach: We applied four centrality measures (degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) and authors' published papers to the scientific collaboration network. The grey relational analysis (GRA) method based on information entropy was used to measure an author's impact in the collaboration network. The weight of each evaluation index was determined based on information entropy. The ACM SIGKDD collaboration network was selected as an example to demonstrate the practicality and effectiveness of our method.
Findings: Author influence was not always positively correlated with evaluation indexes such as degree centrality and betweenness centrality. This implies that combined effects of multiple indexes should be considered in author impact analysis. The introduction of the GRA method based on information entropy can reduce the interference of human factors in the evaluation process.
Research limitations: We only analyzed author influence from the perspective of scientific collaboration, but the impact of citation on author influence was ignored.
Practical implications: The proposed method can be also applied to detect influential authors in bibliographic co-citation network, author co-citation network, bibliographic coupling network or author coupling network. It would help facilitate scientific collaboration and enhance scholarly communication.
Originality/value: This paper proposes an analytical method of evaluating author influence in scientific collaboration networks, in which combined effects of multiple indexes are considered and the interference of human factors is reduced in the evaluation process.
Purpose: The purpose of this paper is to measure author influence in scientific collaboration networks by considering the combined effects of multiple indexes. In the meanwhile, we intend to explore a method to avoid assigning subjective weights.
Design/methodology/approach: We applied four centrality measures (degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) and authors' published papers to the scientific collaboration network. The grey relational analysis (GRA) method based on information entropy was used to measure an author's impact in the collaboration network. The weight of each evaluation index was determined based on information entropy. The ACM SIGKDD collaboration network was selected as an example to demonstrate the practicality and effectiveness of our method.
Findings: Author influence was not always positively correlated with evaluation indexes such as degree centrality and betweenness centrality. This implies that combined effects of multiple indexes should be considered in author impact analysis. The introduction of the GRA method based on information entropy can reduce the interference of human factors in the evaluation process.
Research limitations: We only analyzed author influence from the perspective of scientific collaboration, but the impact of citation on author influence was ignored.
Practical implications: The proposed method can be also applied to detect influential authors in bibliographic co-citation network, author co-citation network, bibliographic coupling network or author coupling network. It would help facilitate scientific collaboration and enhance scholarly communication.
Originality/value: This paper proposes an analytical method of evaluating author influence in scientific collaboration networks, in which combined effects of multiple indexes are considered and the interference of human factors is reduced in the evaluation process.</div
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