240,833 research outputs found
Quantitative assessment of collaboration
No full textSite de l'éditeur : http://www.iisi.de/international-reports-on-socio-informatics-irsi/This paper presents a short literature review of a research trend that endeavors to model collaboration by quantifying each group member‟s contribution. In such a view, equity is considered as the ideal collaborative situation. We review some foundational elements of this approach, some methodological aspects, describe a case study applying such concepts and analyses, and present examples of design implications for Computer-Supported Cooperative Work
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
R&D collaboration with uncertain intellectual property rights.
No full textPatent pendencies create uncertainty in research and development (R&D) collaboration agreements, resulting in a threat of expropriation of unprotected knowledge by potential partners, reduced bargaining power and enhanced search costs. In this paper, we show that - depending of the type of partner - uncertain intellectual property rights (IPR) lead to reduced collaboration between firms and may hinder the production of knowledge. This has implications for technology policy as R&D collaborations are exempt from anti-trust legislation in order to increase R&D in the economy. We argue that a functional IPR system is needed for successful utilization of this policy.R&D collaboration; intellectual property; uncertainty; patents;
R&D collaboration with uncertain intellectual property rights
No full textPatent pendencies create uncertainty in research and development (R&D) collaboration agreements, resulting in a threat of expropriation of unprotected knowledge by potential partners, reduced bargaining power and enhanced search costs. In this paper, we show that - depending of the type of partner - uncertain intellectual property rights (IPR) lead to reduced collaboration between firms and may hinder the production of knowledge. This has implications for technology policy as R&D collaborations are exempt from anti-trust legislation in order to increase R&D in the economy. We argue that a functional IPR system is needed for successful utilization of this policy. --R&D collaboration,intellectual property,uncertainty,patents
Measurement of the D+/- production asymmetry in 7 TeV pp collisions
No full textThe asymmetry in the production cross-section \sigma of D+/- mesons, A_P = (\sigma(D+) - \sigma(D-))/(\sigma(D+) + \sigma(D-)), is measured in bins of pseudorapidity \eta and transverse momentum p_T within the acceptance of the LHCb detector. The result is obtained with a sample of D+ -> K_S pi+ decays corresponding to an integrated luminosity of 1.0 fb^-1, collected in pp collisions at a centre of mass energy of 7 TeV at the Large Hadron Collider. When integrated over the kinematic range 2.0 K_S pi+ decay is negligible. No significant dependence on \eta or p_T is observed
Coauthor prediction for junior researchers
No full textResearch collaboration can bring in different perspectives and generate more productive results. However, finding an appropriate collaborator can be difficult due to the lacking of sufficient information. Link prediction is a related technique for collaborator discovery; but its focus has been mostly on the core authors who have relatively more publications. We argue that junior researchers actually need more help in finding collaborators. Thus, in this paper, we focus on coauthor prediction for junior researchers. Most of the previous works on coauthor prediction considered global network feature and local network feature separately, or tried to combine local network feature and content feature. But we found a significant improvement by simply combing local network feature and global network feature. We further developed a regularization based approach to incorporate multiple features simultaneously. Experimental results demonstrated that this approach outperformed the simple linear combination of multiple features. We further showed that content features, which were proved to be useful in link prediction, can be easily integrated into our regularization approach. © 2013 Springer-Verlag
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
The Relationship between R&D Collaboration, Subsidies and Patenting Activity: Empirical Evidence from Finland and Germany
No full textThis study focuses on the impact of innovation policies and R&D collaboration in Germany and Finland. We consider collaboration and subsidies as heterogeneous treatments, and perform an econometric matching to analyze R&D and patent activity at the firm level. In general, we find that collaboration has positive effects. In Germany, subsidies for individual research do not exhibit a significant impact neither on R&D nor patenting, but the innovative performance could be improved by additional incentives for collaboration. For Finnish companies, public funding is an important source of finance for R&D. Without subsidies, recipients would show less R&D and patenting activity, whilst those firms not receiving subsidies would perform significantly better if they were publicly funded. --R&D,Public Subsidies,Collaboration,Policy Evaluation
Measurement of the B0–B0 oscillation frequency Δmd with the decays B0→D−π+ and B0→ J/ψK∗0
No full textThe B
0
–B
0
oscillation frequency Δmd is measured by the LHCb experiment using a dataset corresponding
to an integrated luminosity of 1.0 fb−1
of proton–proton collisions at √
s = 7 TeV, and is found to be
Δmd
=0.5156±0.0051 (stat.)±0.0033 (syst.) ps−1
. The measurement is based on results from analyses
of the decays B
0
→ D
−π
+ (D
−
→ K
+π
−π
−) and B
0
→ J/ψK
∗0
(J/ψ →μ
+μ
−,K
∗0
→ K
+π
−) and
their charge conjugated modes
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
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