Authors:Shahadat Uddin, Liaquat Hossain, Alireza Abbasi, and Kim Rasmussen
-authorship. Co-authorshipnetworks are an important class of social networks and have been analyzed extensively, both at network level and individual node level, to explore different statistical characteristics (Newman 2001 ) and behavioural patterns of
; Beaver and Rosen 1978 ).
Co-authorshipnetwork analysis has been widely used to study the cooperation of research groups in many disciplines. However, few researches have focused on the emergence of medical co-authorshipnetworks in China. The
Authors:Zaida Chinchilla-Rodríguez, Anuska Ferligoj, Sandra Miguel, Luka Kronegger, and Félix de Moya-Anegón
collaboration networks in four subject areas.
Building on these studies, the present research focuses on dynamic co-authorshipnetworks in the specific field of information science in a Latin American country from 2001 to 2009. The blockmodeling approach
We analyse the co-authorship networks of researchers affiliated at universities in Turkey by using two databases: the international
SSCI database and the Turkish ULAKBIM database. We find that co-authorship networks are composed largely of isolated groups
and there is little intersection between the two databases, permitting little knowledge diffusion. There seems to be two disparate
populations of researchers. While some scholars publish mostly in the international journals, others target the national audience,
and there is very little intersection between the two populations. The same observation is valid for universities, among which
there is very little collaboration. Our results point out that while Turkish social sciences and humanities publications have
been growing impressively in the last decade, domestic networks to ensure the dissemination of knowledge and of research output
are very weak and should be supported by domestic policies.
Authors:Antonio Perianes-Rodríguez, Carlos Olmeda-Gómez, and Félix Moya-Anegón
The present paper proposes a method for detecting, identifying and visualizing research groups. The data used refer to nine
Carlos III University of Madrid departments, while the findings for the Communication Technologies Department illustrate the
method. Structural analysis was used to generate co-authorship networks. Research groups were identified on the basis of factorial
analysis of the raw data matrix and similarities in the choice of co-authors. The resulting networks distinguished the researchers
participating in the intra-departmental network from those not involved and identified the existing research groups. Fields
of research were characterized by the Journal of Citation Report subject category assigned to the bibliographic references
cited in the papers written by the author-factors. The results, i.e., the graphic displays of the structures of the socio-centric
and co-authorship networks and the strategies underlying collaboration among researchers, were later discussed with the members
of the departments analyzed. The paper constitutes a starting point for understanding and characterizing networking within
Authors:Fuyuki Yoshikane, Takayuki Nozawa, and Keita Tsuji
Many studies have analyzed “direct” partnerships in co-authorship networks. On the other hand, the global network structure,
including “indirect” links between researchers, has not yet been sufficiently studied. This study analyzes researchers' activities
from the viewpoints considering their roles in the global structures of co-authorship networks, and compares the co-authorship
networks between the theoretical and application areas in computer science. The modified HITS algorithm is used to calculate
the two types of importance of researchers in co-authorship networks, i.e., the importance as the leader and that as the follower.
Although there are many measures of centrality of individuals in social networks, and those centrality measures can be applied
to the analysis of authors’ importance in co-authorship networks, the distribution of an author’s collaborative relationships
among different communities has not been considered. This distribution or extensity is an important aspect of authors’ activity.
In the present study, we will propose a new measure termed extensity centrality, taking into account the distribution of an
author’s collaborative relationships. In computing the strength of collaborative ties, which is closely related to the extensity
centrality, we choose Salton’s measure. We choose the ACM SIGKDD data as our testing data set, and analyze the result of authors’
importance from different points of view.
Authors:Theresa Velden, Asif-ul Haque, and Carl Lagoze
This paper focuses on methods to study patterns of collaboration in co-authorship networks at the mesoscopic level. We combine
qualitative methods (participant interviews) with quantitative methods (network analysis) and demonstrate the application
and value of our approach in a case study comparing three research fields in chemistry. A mesoscopic level of analysis means
that in addition to the basic analytic unit of the individual researcher as node in a co-author network, we base our analysis
on the observed modular structure of co-author networks. We interpret the clustering of authors into groups as bibliometric
footprints of the basic collective units of knowledge production in a research specialty. We find two types of coauthor-linking
patterns between author clusters that we interpret as representing two different forms of cooperative behavior, transfer-type
connections due to career migrations or one-off services rendered, and stronger, dedicated inter-group collaboration. Hence
the generic coauthor network of a research specialty can be understood as the overlay of two distinct types of cooperative
networks between groups of authors publishing in a research specialty. We show how our analytic approach exposes field specific
differences in the social organization of research.
Authors:Hildrun Kretschmer, Ute Kretschmer, and Theo Kretschmer
About ten years ago a new research field called “webometrics” emerged. Similarities between methods used in webometrics and
scientometrics or informetrics are evident from the literature. Are there also similarities between scientometric and Web
indicators of collaboration for possible use in technology policy making? Usually, the bibliometric method used to study collaboration
is the investigation of co-authorships.
In this paper, Web hyperlinks and Web visibility indicators are examined to establish their usefulness as indicators of collaboration
and to explore whether similarities exist between Web-based structures and bibliographic structures.
Three empirical studies of collaboration between institutions and individual scientists show that hyperlink structures at
the Web don’t reflect collaboration structures collected by bibliographic data. However Web visibility indicators of collaboration
are different from hyperlinks and can be successfully used as Web indicators of collaboration.