32,607 research outputs found
Betweenness Centrality as a Driver of Preferential Attachment in the Evolution of Research Collaboration Networks
We analyze whether preferential attachment in scientific coauthorship
networks is different for authors with different forms of centrality. Using a
complete database for the scientific specialty of research about "steel
structures," we show that betweenness centrality of an existing node is a
significantly better predictor of preferential attachment by new entrants than
degree or closeness centrality. During the growth of a network, preferential
attachment shifts from (local) degree centrality to betweenness centrality as a
global measure. An interpretation is that supervisors of PhD projects and
postdocs broker between new entrants and the already existing network, and thus
become focal to preferential attachment. Because of this mediation, scholarly
networks can be expected to develop differently from networks which are
predicated on preferential attachment to nodes with high degree centrality.Comment: Journal of Informetrics (in press
Collaboration in an Open Data eScience: A Case Study of Sloan Digital Sky Survey
Current science and technology has produced more and more publically
accessible scientific data. However, little is known about how the open data
trend impacts a scientific community, specifically in terms of its
collaboration behaviors. This paper aims to enhance our understanding of the
dynamics of scientific collaboration in the open data eScience environment via
a case study of co-author networks of an active and highly cited open data
project, called Sloan Digital Sky Survey. We visualized the co-authoring
networks and measured their properties over time at three levels: author,
institution, and country levels. We compared these measurements to a random
network model and also compared results across the three levels. The study
found that 1) the collaboration networks of the SDSS community transformed from
random networks to small-world networks; 2) the number of author-level
collaboration instances has not changed much over time, while the number of
collaboration instances at the other two levels has increased over time; 3)
pairwise institutional collaboration become common in recent years. The open
data trend may have both positive and negative impacts on scientific
collaboration.Comment: iConference 201
International Collaboration in Science and the Formation of a Core Group
International collaboration as measured by co-authorship relations on
refereed papers grew linearly from 1990 to 2005 in terms of the number of
papers, but exponentially in terms of the number of international addresses.
This confirms Persson et al.'s (2004) hypothesis of an inflation in
international collaboration. Patterns in international collaboration in science
can be considered as network effects, since there is no political institution
mediating relationships at that level except for the initiatives of the
European Commission. During the period 2000-2005, the network of global
collaborations appears to have reinforced the formation of a core group of
fourteen most cooperative countries. This core group can be expected to use
knowledge from the global network with great efficiency, since these countries
have strong national systems. Countries at the periphery may be disadvantaged
by the increased strength of the core
An exploratory social network analysis of academic research networks
For several decades, academics around the world have been collaborating with the view to support the development of their research domain. Having said that, the majority of scientific and technological policies try to encourage the creation of strong inter-related research groups in order to improve the efficiency of research outcomes and subsequently research funding allocation. In this paper, we attempt to highlight and thus, to demonstrate how these collaborative networks are developing in practice. To achieve this, we have developed an automated tool for extracting data about joint article publications and analyzing them from the perspective of social network analysis. In this case study, we have limited data from works published in 2010 by England academic and research institutions. The outcomes of this work can help policy makers in realising the current status of research collaborative networks in England
The Complex Network of Evolutionary Computation Authors: an Initial Study
EC paper authors form a complex network of co-authorship which is, by itself,
a example of an evolving system with its own rules, concept of fitness, and
patterns of attachment. In this paper we explore the network of authors of
evolutionary computation papers found in a major bibliographic database. We
examine its macroscopic properties, and compare it with other co-authorship
networks; the EC co-authorship network yields results in the same ballpark as
other networks, but exhibits some distinctive patterns in terms of internal
cohesion. We also try to find some hints on what makes an author a sociometric
star. Finally, the role of proceeding editorship as the origin of long-range
links in the co-authorship network is studied as well.Comment: Sociometric study of the Evolutionary Computation community.
Submitted to Evolutionary Computation lette
Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists
Scientific collaborations shape ideas as well as innovations and are both the
substrate for, and the outcome of, academic careers. Recent studies show that
gender inequality is still present in many scientific practices ranging from
hiring to peer-review processes and grant applications. In this work, we
investigate gender-specific differences in collaboration patterns of more than
one million computer scientists over the course of 47 years. We explore how
these patterns change over years and career ages and how they impact scientific
success. Our results highlight that successful male and female scientists
reveal the same collaboration patterns: compared to scientists in the same
career age, they tend to collaborate with more colleagues than other
scientists, seek innovations as brokers and establish longer-lasting and more
repetitive collaborations. However, women are on average less likely to adapt
the collaboration patterns that are related with success, more likely to embed
into ego networks devoid of structural holes, and they exhibit stronger gender
homophily as well as a consistently higher dropout rate than men in all career
ages
Coauthorship and Thematic Networks in AAEP Annual Meetings
We analyze the coauthorship production of the AAEP Annual Meeting since 1964.
We use social network analysis for creating coauthorship networks and given
that any paper must be tagged with two JEL codes, we use this information for
also structuring a thematic network. Then we calculate network metrics and find
main actors and clusters for coauthors and topics. We distinguish a gender gap
in the sample. Thematic networks show a cluster of codes and the analysis of
the cluster shows the preeminence of the tags related to trade, econometric,
distribution/poverty and health and education topics.Comment: 30 pages, 12 Figures, 16 Table
Mapping the Evolution of "Clusters": A Meta-analysis
This paper presents a meta-analysis of the âcluster literatureâ contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a âspatialâ and an âindustrialâ approach within the textual corpus of cluster literature and we show the existence of a âpredatoryâ interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship
Recent Trends on Liquid Air Energy Storage: A Bibliometric Analysis
The increasing penetration of renewable energy has led electrical energy storage systems to have a key role in balancing and increasing the e ciency of the grid. Liquid air energy storage (LAES) is a promising technology, mainly proposed for large scale applications, which uses cryogen (liquid air) as energy vector. Compared to other similar large-scale technologies such as compressed air energy storage or pumped hydroelectric energy storage, the use of liquid air as a storage medium allows a high energy density to be reached and overcomes the problem related to geological constraints. Furthermore, when integrated with high-grade waste cold/waste heat resources such as the liquefied natural gas regasification process and hot combustion gases discharged to the atmosphere, LAES has the capacity to significantly increase the round-trip efficiency. Although the first document in the literature on the topic of LAES appeared in 1974, this technology has gained the attention of many researchers around the world only in recent years, leading to a rapid increase in a scientific production and the realization of two system prototype located in the United Kingdom (UK). This study aims to report the current status of the scientific progress through a bibliometric analysis, defining the hotspots and research trends of LAES technology. The results can be used by researchers and manufacturers involved in this entering technology to understand the state of art, the trend of scientific production, the current networks of worldwide institutions, and the authors connected through the LAES. Our conclusions report useful advice for the future research, highlighting the research trend and the current gaps.This work was partially funded by the Ministerio de Ciencia, InnovaciĂłn y Universidades de España (RTI2018-093849-B-C31âMCIU/AEI/FEDER, UE). This work was partially funded by the Ministerio de Ciencia, InnovaciĂłn y Universidades - Agencia Estatal de InvestigaciĂłn (AEI) (RED2018-102431-T).
The authors at the University of Lleida would like to thank the Catalan Government for the quality accreditation given to their research group GREiA (2017 SGR 1537). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia. This work was partially supported by ICREA under the ICREA Academia program
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